Dissertations / Theses: 'QSAR'

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Espinosa, Porragas Gabriela. "Modelos QSPR/QSAR/QSTR basados en sistemas neuronales cognitivos." Doctoral thesis, Universitat Rovira i Virgili, 2002. http://hdl.handle.net/10803/8505.

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Un área sumamente interesante dentro del modelado molecular es el diseño de nuevos compuestos. Con sus propiedades definidas antes de ser sintetizados. Los métodos QSPR/QSAR han demostrado que las relaciones entre la estructura molecular y las propiedades físico químicas o actividades biológicas de los compuestos se pueden cuantificar matemáticamente a partir de parámetros estructurales simples.
Las redes neuronales (ANN) constituyen una alternativa para el desarrollo de algoritmos predictivos aplicados en diversos campos como: análisis masivo de bases de datos, para subsanar los obstáculos derivados de la selección o la multicolinealidad de variables, así como la sensibilidad de los modelos a la presencia de ruido en los datos de entrada al sistema neuronal. En la mayoría de los casos, las redes neuronales han dado mejores resultados que los métodos de regresión multilineal (MLR), el análisis de componentes principales (PCA), o los métodos de mínimos cuadrados parciales (PLS) debido a la no linealidad inherente en los modelos de redes.

En los últimos años el interés por los modelos QSPR/QSAR basados en redes neuronales se ha incrementado. La principal ventaja de los modelos de redes recae en el hecho que un modelo QSAR/QSPR puede desarrollarse sin especificar a priori la forma analítica del modelo. Las redes neuronales son especialmente útiles para establecer las complejas relaciones existentes entre la salida del modelo (propiedades físico químicas o biológicas) y la entrada del modelo (descriptores moleculares). Además, permiten clasificar los compuestos de acuerdo a sus descriptores moleculares y usar esta información para seleccionar el conjunto de índices capaz de caracterizar mejor al conjunto de moléculas. Los modelos QSPR basados en redes usan principalmente algoritmos del tipo backpropagation. Backpropagation es un sistema basado en un aprendizaje por minimización del error. Sin embargo, ya que los compuestos químicos pueden clasificarse en grupos de acuerdo a su similitud molecular, es factible usar un clasificador cognitivo como fuzzy ARTMAP para crear una representación simultánea de la estructura y de la propiedad objetivo. Este tipo de sistema cognitivo usa un aprendizaje competitivo, en el cual hay una activa búsqueda de la categoría o la hipótesis cuyos prototipos provean una mejor representación de los datos de entrada (estructura química).

En el presente trabajo se propone y se estudia una metodología que integra dos sistemas cognitivos SOM y fuzzy ARTMAP para obtener modelos QSAR/QSPR. Los modelos estiman diferentes propiedades como las temperaturas de transición de fase (temperatura de ebullición, temperatura de fusión) y propiedades críticas (temperatura y presión), así como la actividad biológica de compuestos orgánicos diversos (indicadores de toxicidad). Dentro de este contexto, se comparan la selección de variables realizados por métodos tradicionales (PCA, o métodos combinatorios) con la realizada usando mapas auto-organizados (SOM).

El conjunto de descriptores moleculares más factible se obtiene escogiendo un representante de cada categoría de índices, en particular aquel índice con la correlación más alta con respecto a la propiedad objetivo. El proceso continúa añadiendo índices en orden decreciente de correlación. Este proceso concluye cuando una medida de disimilitud entre mapas para los diferentes conjuntos de descriptores alcanza un valor mínimo, lo cual indica que el añadir descriptores adicionales no provee información complementaria a la clasificación de los compuestos estudiados. El conjunto de descriptores seleccionados se usa como vector de entrada a la red fuzzy ARTMAP modificada para poder predecir.

Los modelos propuestos QSPR/QSAR para predecir propiedades tanto físico químicas como actividades biológicas predice mejor que los modelos obtenidos con métodos como backpropagation o métodos de contribución de grupos en los casos en los que se apliquen dichos métodos.
One of the most attractive applications of computer-aided techniques in molecular modeling stands on the possibility of assessing certain molecular properties before the molecule is synthesized. The field of Quantitative Structure Activity/Property Relationships (QSAR/QSPR) has demonstrated that the biological activity and the physical properties of a set of compounds can be mathematically related to some "simple" molecular structure parameters.

Artificial neural network (ANN) approaches provide an alternative to established predictive algorithms for analyzing massive chemical databases, potentially overcoming obstacles arising from variable selection, multicollinearity, specification of important parameters, and sensitivy to erroneous values. In most instances, ANN's have proven to be better than MLR, PCA or PLS because of their ability to handle non-linear associations.

In the last years there has been a growing interest in the application of neural networks to the development of QSAR/QSPR. The mayor advantage of ANN lies in the fact QSAR/QSPR can be developed without having to a priori specify an analytical form for the correlation model. The NN approach is especially suited for mapping complex non-linear relationships that exists between model output (physicochemical or biological properties) and input model (molecular descriptors). The NN approach could also be used to classify chemicals according to their chemical descriptors and used this information to select the most suitable indices capable of characterize the set of molecules. Existing neural networks based QSAR/QSPR for estimating properties of chemicals have relied primarily on backpropagation architecture. Backpropagation are an error based learning system in which adaptive weights are dynamically revised so as to minimize estimation errors of target values. However, since chemical compounds can be classified into various structural categories, it is also feasible to use cognitive classifiers such as fuzzy ARTMAP cognitive system, for unsupervised learning of categories, which represent structure and properties simultaneously. This class of neural networks uses a match-based learning, in that it actively searches for recognition categories or hypotheses whose prototype provides an acceptable match to input data.

The current study have been proposed a new QSAR/QSPR fuzzy ARTMAP neural network based models for predicting diverse physical properties such as phase transition temperatures (boiling and melting points) and critical properties (temperature and pressure) and the biological activities (toxicity indicators) of diverse set of compounds. In addition, traditional pre-screening methods to determine de minimum set of inputs parameters have been compared with novel methodology based in self organized maps algorithms.

The most suitable set of molecular descriptor was obtained by choosing a representative from each cluster, in particular the index that presented the highest correlation with the target variable, and additional indices afterwards in order of decreasing correlation. The selection process ended when a dissimilarity measure between the maps for the different sets of descriptors reached a minimum valued, indicating that the inclusion of more descriptors did not add supplementary information. The optimal subset of descriptors was finally used as input to a fuzzy ARTMAP architecture modified to effect predictive capabilities.

The proposed QSPR/QSAR model predicted physicochemical or biological activities significantly better than backpropagation neural networks or traditional approaches such as group contribution methods when they applied.

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Al-Fahemi, Jabir Hamad. "Momentum-space descriptors for QSPR and QSAR studies." Thesis, University of Liverpool, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439465.

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Arruda, Anna Celia. "Ampliação e aplicação do método semi-empírico topológico (IET) em modelos QSRR/QSPR/QSAR para compostos alifáticos halogenados e cicloalcanos." Florianópolis, SC, 2008. http://repositorio.ufsc.br/xmlui/handle/123456789/91111.

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Tese (doutorado) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas. Programa de Pós-Graduação em Química.
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Este estudo foi desenvolvido para avaliar a capacidade de prognóstico do índice semi-empírico topológico (IET) em estimar a retenção cromatográfica (IR) de compostos alifáticos halogenados e cicloalcanos. Também foram desenvolvidos modelos de QSPR/QSAR para prever importantes propriedades físico-químicas, termodinâmicas e atividades biológicas. O modelo de QSRR do IRExpde 141 haloalcanos e o IET mostrou boa qualidade estatística (r2=0,9995; SD=8; r2cv=0,999). A partir do modelo de QSPR obtido entre o ponto de ebulição, Bp(ºC), com o IET (N=86; r2=0,9971; SD=4,2; r2cv=0,997), foram calculados os valores para um grupo externo de 24 compostos (r2=0,9931; SD=7,6). Uma boa correlação entre o ponto de fusão, Mp (°C), e o IET foi obtida (N=43; r2=0,9865; SD=6,1; r2cv=0,985). As correlações obtidas entre os valores calculados e experimentais de log P foram de r2=0,9871 e r2=0,9750, respectivamente para os Métodos Semi-Empírico Topológico e Contribuição dos Fragmentos. Esses resultados mostram a capacidade de prognóstico do IET para propriedades físico-químicas e termodinâmicas. A habilidade de prognóstico do IR pelo IET também foi verificada usando fases estacionárias com diferentes polaridades. Resultados satisfatórios foram encontrados aplicando o IET para estimar o IR de 48 cicloalcanos (r2=0,9905; SD=7; r2cv=0,997) e Bp(°C) (N=33; r2cv=0,988). Esse método permitiu retirar informações sobre as características estruturais, eletrônicas e geométricas das moléculas que estão influenciando no processo de retenção cromatográfico e a distinção entre isômeros cis/trans dos compostos estudados.

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Davor, Lončar. "Definisanje lipofilnosti, farmakokinetičkih parametara i antikancerogenog potencijala novosintetisane serije stiril laktona." Phd thesis, Univerzitet u Novom Sadu, Tehnološki fakultet Novi Sad, 2018. https://www.cris.uns.ac.rs/record.jsf?recordId=107622&source=NDLTD&language=en.

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Reverzno-faznom tečnom hromatografijom pod visokim pritiskom primenom dva sistemarastvarača ispitano je ponašanje i hromatografska lipofilnost prirodnih stiril laktona 7-(+)-goniofufurona, 7-epi-(+)-goniofufurona, krasalaktona B i C i dvadeset njihovihnovosintetizovanih derivata i analoga. U ranijim ispitivanjima pokazalo se da ova jedinjenjaimaju veliki biološki potencijal jer pokazuju zapaženu citotoksičnost prema više humanihtumorskih ćelijskih linija. Hromatografsko ponašanje jedinjenja uglavnom je u skladu sanjihovom strukturom. Ustanovljene su linearne veze između hromatografskih retencionihkonstanti i većine in silico parametara lipofilnosti. Primenom hemometrijske QSRR analizeutvrđeni su veoma dobri multi linearni regresioni prediktivni modeli kvantitativne zavisnostiizmeđu eksperimentalno dobijene hromatografske retencione konstante, koja definišeretenciju jedinjenja u čistoj vodi i in silico molekulskih deskriptora odnosno strukturejedinjenja. Lipofilnost jedinjenja ima najveći uticaj na njihove farmakokinetičke, tj. ADME(apsorpcija, distribucija, metabolizam, eliminacija) osobine. Definisani su i statističkipotvrđeni najbolji multi linearni regresioni modeli zavisnosti farmakokinetičkih parametarastiril laktona i od drugih molekulskih deskriptora. In vitro citotoksična aktivnost jedinjenjaevaluirana je prema četiri nove humane maligne ćelijske linije: kancer prostate (PC3), kancer debelog creva (HT-29), melanom (Hs294T), adenokancer pluća (A549). Najaktivnijenovosintetizovano jedinjenje je triciklični 4-fluorocinamatni analog, koji ispoljavananomolarnu aktivnost (IC₅₀ 2,1 nM) prema ćelijama melanoma i aktivniji je preko 2250 puta od komercijalnog antitumorskog agensa doksorubicina (DOX). SAR analizom utvrđena je zavisnost između strukture i biološke aktivnosti jedinjenja. Molekulskim dokingom ispitana je veza stiril laktona i ciljanog proteina značajnog za kancer prostate. Jedinjenja sa visokom inhibitornom aktivnošću prema ćelijama kancera prostate imaju visok doking skor i mogu graditi koordinativno-kovalentnu vezu sa Fe²+jonom prisutnim u aktivnom centru enzima. 3D-QSAR analizom, koja je izvedena metodama komparativnih polja CoMFA i CoMSIA, formiran je značajan prediktivni model između hemijske strukture i biološke aktivnosti stiril laktona.
The behavior and the chromatographic lipophilicity natural styryl lactone 7-(+)-goniofufurone, 7-epi-(+)-goniofufurone, crassalactones B and C and twenty of their newlysynthesized derivatives and analogs were examined using reverse-phase high performance liquid chromatography in the two solvent systems. In previous studies it has been shown that these compounds have great biological potential toward several human tumor cell lines. Chromatographic behavior of the compounds is generally in accordance with their structure. The relationships between the chromatographic retention constants and the majority of their in silico lipophilicity parameters are linear. The application of chemometric QSRR analysis determined very good multiple linear regression predictive models of quantitative correlation between experimentally obtained chromatographic retention constant, which determines the retention of the compound in pure water and in silico molecular descriptors, i.e. the structure of the compound. The lipophilicity of the compounds has a major influence on their pharmacokinetics, i.e. ADME (absorption, distribution, metabolism, elimination) properties. The best multi-linear regression models depending on the pharmacokinetic parameters of styryl lactone and other molecular descriptors have been defined and statistically validated. In vitro cytotoxic activity of the compounds was evaluated according to four novel human malignant cell lines: prostate cancer (PC3), colon cancer (HT-29), melanoma (Hs294T), lung adenocarcinom (A549). The most active compound was tricyclic 4-fluorocinnamic analog, which exhibits a nanomolar activity (IC50 2,1 nM) toward melanoma cells. This compound is over 2250 times more active than commercial antitumor agent doxorubicin (DOX). SAR analysis has revealed a correlation between the structure and the biological activity of the compounds. Using the molecular docking the relationship of the styryl lactone and the target protein important for prostate cancer was examined. The compounds with high inhibitory activity against prostate cancer cells have a high docking score and are capable to form a coordinative-covalent bond with a Fe2+ ion present in the active centre of the enzyme. 3DQSAR analysis, which was performed by methods of comparative CoMFA and CoMSIA fields, has formed a good predictive model between chemical structure and biological activity of the styryl lactone.

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Bitencourt, Michelle 1985. "Modelagem MIA-QSAR de inibidores de acetilcolinesterase = MIA-QSAR modeling of inhibitors actylcholinesterase." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/311808.

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Orientador: Roberto Rittner Neto
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas
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Resumo: O presente trabalho trata de um estudo sobre compostos que se comportam como inibidores da acetilcolinesterase, uma importante enzima do processo de cognição. A acetilcolinesterase atua na hidrólise da acetilcolina, responsável pela comunicação entre os neurônios. Uma das modalidades para o design racional de fármacos é a estimativa de propriedades biológicas de novas moléculas utilizando métodos computacionais. Análise quantitativa entre estrutura química e atividade biológica (QSAR) é uma dessas técnicas. No presente trabalho, análise multivariada de imagens aplicada em QSAR (MIA-QSAR) foi utilizada para se construírem modelos QSAR preditivos para uma série congênere de carbamatos com atividade anticolinesterásica. Os bons resultados estatísticos da modelagem credenciaram o modelo MIA-QSAR construído a predizer a atividade biológica de alguns novos derivados, potencialmente úteis para o tratamento do Mal de Alzheimer
Abstract: The present work describes the study of some compounds which act as acetylcholinesterase inhibitors a very important enzyme in the cognitive process. zAcetylcholinesterase is responsible by the hydrolysis of acetylcholine, which accounts for the communication among the neurons. One of the approaches for the rational pharmaceuticals design is the estimation of the biological properties of new molecules using computational methods. The quantitative analysis between chemical structure and biological activity (QSAR) is one of these techniques. In the present work, the multivariate analysis of images applied in QSAR (MIA-QSAR) was employed for building predictable QSAR models for a congenial series of carbamates which exhibit anticholinesterase activity. The significant statistical results from this treatment enabled the MIA-QSAR model thus obtained to reliably predict the biological activity of some new derivatives, as potentially useful for the Alzheimer Disease treatment
Mestrado
Ciencias Biomedicas
Mestra em Ciências Médicas

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Martins, João Paulo Ataíde 1980. "Desenvolvimento de softwares, algoritmos e diferentes abordagens quimiométricas em estudos de QSAR." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/248544.

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Orientador: Márcia Miguel Castro Ferreira
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química
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Resumo: O planejamento de fármacos com o auxílio do computador é uma área de pesquisa de extrema importância em química e áreas correlatas. O conjunto de ferramentas disponíveis para tal fim consiste, dentre outras, em programas para geração de descritores e construção e validação de modelos matemáticos em QSAR (do inglês, Quantitative Structure-Activity Relationship). Com o objetivo de tornar esse estudo mais acessível para a comunidade científica, novas metodologias e programas para geração de descritores e construção e validação de modelos QSAR foram desenvolvidos nessa tese. Uma nova metodologia de QSAR 4D, conhecida com LQTA-QSAR, foi desenvolvida com o objetivo de gerar descritores espaciais levando em conta os perfis de amostragem conformacional das moléculas em estudo obtidos a partir de simulações de dinâmica molecular. A geração desses perfis é feita com o software livre GROMACS e os descritores são gerados a partir de um novo software desenvolvido nesse trabalho, chamado de LQTAgrid. Os resultados obtidos com essa metodologia foram validados comparando-os com resultados obtidos para conjuntos de dados disponíveis na literatura. Um outro software de fácil uso, e que engloba as principais ferramentas de construção e validação de modelos em QSAR, foi desenvolvido e chamado de QSAR modeling. Esse software implementa o método de seleção de variáveis OPS, desenvolvido em nosso laboratório, e utiliza PLS (do inglês Partial Least Squares) como método de regressão. A escolha do algoritmo PLS implementado no programa foi feita com base em um estudo sobre o desempenho e a precisão no erro de validação dos principais algoritmos PLS disponíveis na literatura. Além disso, o programa QSAR modeling foi utilizado em um estudo de QSAR 2D para um conjunto de 20 flavonóides com atividade anti-mutagênica contra 3-nitrofluoranteno (3-NFA)
Abstract: Computer aided drug design is an important research field in chemistry and related areas. The available tools used in such studies involve software to generate molecular descriptors and to build and validate mathematical models in QSAR (Quantitative Structure-Activity Relationship). A new set of methodologies and software to generate molecular descriptors and to build and validate QSAR models were developed aiming to make these kind of studies more accessible to scientific community. A new 4DQSAR methodology, known as LQTA-QSAR, was developed with the purpose to generate spatial descriptors taking into account conformational ensemble profile obtained from molecular dynamics simulations. The generation of these profiles is performed by free software GROMACS and the descriptors are generated by a new software developed in this work, called LQTAgrid. The results obtained with this methodology were validated comparing them with results available in literature. Another user friendly software, which contains some of the most important tools used to build and validate QSAR models was developed and called QSAR modeling. This software implements the OPS variable selection algorithm, developed in our laboratory, and uses PLS (Partial Least Squares) as regression method. The choice of PLS algorithm implemented in the program was performed by a study about the performance and validation precision error involving the most important PLS algorithms available in literature. Further, QSAR modeling was used in a 2D QSAR study with 20 flavonoid derivatives with antimutagenic activity against 3-nitrofluoranthene (3-NFA)
Doutorado
Físico-Química
Doutor em Ciências

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Hellberg, Sven. "A multivariate approach to QSAR." Doctoral thesis, Umeå universitet, Kemiska institutionen, 1986. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-100713.

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Quantitative structure-activity relationships (OSAR) constitute empirical analogy models connecting chemical structure and biological activity. The analogy approach to QSAR assume that the factors important in the biological system also are contained in chemical model systems. The development of a QSAR can be divided into subproblems: 1. to quantify chemical structure in terms of latent variables expressing analogy, 2. to design test series of compounds, 3. to measure biological activity and 4. to construct a mathematical model connecting chemical structure and biological activity. In this thesis it is proposed that many possibly relevant descriptors should be considered simultaneously in order to efficiently capture the unknown factors inherent in the descriptors. The importance of multivariately and multipositionally varied test series is discussed. Multivariate projection methods such as PCA and PLS are shown to be appropriate far QSAR and to closely correspond to the analogy assumption. The multivariate analogy approach is applied to a beta- adrenergic agents, b haloalkanes, c halogenated ethyl methyl ethers and d four different families of peptides.

Diss. (sammanfattning) Umeå : Umeå universitet, 1986, härtill 8 uppsatser

digitalisering@umu

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Moda, Tiago Luiz. "Desenvolvimento de modelos in silico de propriedades de ADME para a triagem de novos candidatos a fármacos." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/76/76132/tde-22032007-112055/.

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As ferramentas de modelagem molecular e de estudos das relações quantitativas entre a estrutura e atividade (QSAR) ou estrutura e propriedade (QSPR) estão integradas ao processo de planejamento de fármacos, sendo de extremo valor na busca por novas moléculas bioativas com propriedades farmacocinéticas e farmacodinâmicas otimizadas. O trabalho em Química Medicinal realizado nesta dissertação de mestrado teve como objetivo estudar as relações quantitativas entre a estrutura e as propriedades farmacocinéticas biodisponibilidade oral e ligação às proteínas plasmáticas. Para a realização deste trabalho, conjuntos padrões de dados foram organizados para as propriedades biodisponibilidade e ligação às proteínas plasmáticas contendo a informação qualificada sobre a estrutura química e a propriedade alvo correspondente. Os conjuntos de dados criados formaram as bases científicas para o desenvolvimento dos modelos preditivos empregando os métodos holograma QSAR e VolSurf. Os modelos finais de HQSAR e VolSurf gerados neste trabalho possuem elevada consistência interna e externa, apresentando bom poder de correlação e predição das propriedades alvo. Devido à simplicidade, robustez e consistência, estes modelos são guias úteis em Química Medicinal nos estágios iniciais do processo de descoberta e desenvolvimento de fármacos.
Molecular modeling tools and quantitative structure-activity relantionships (QSAR) or structure-property (QSPR) are integrated into the drug design process in the search for new bioactive molecules with good pharmacokinetic and pharmacodynamic properties. The Medicinal Chemistry work carried out in this Masters dissertation concerned studies of the quantitative relationshisps between chemical structure and the pharmacokinetic properties oral bioavailability and plasma protein binding. In the present work, standard data sets for bioavailability and plasma protein binding were organized encompassing the structural information and corresponding pharmacokinetic data. The created data sets established the scientific basis for the development of predictive models using the hologram QSAR and VolSurf methods. The final HQSAR and VolSurf models posses high internal and external consistency with good correlative and predictive power. Due to the simplicity, robustness and effectivess, these models are useful guides in Medicinal Chemistry in the early stages of the drug discovery and development process.

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Bartlett, Alison. "QSAR study of immunotoxicity in antibiotics." Thesis, Liverpool John Moores University, 1995. http://researchonline.ljmu.ac.uk/5135/.

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Since their inception the B-Iactam antibiotics have become one of the most important classes of phannaceutical agents, both therapeutically and economically, in modern day usage for the treatment of a wide spectrum of bacterial infections. However, due to the versatility of bacteria many previously treatable species are developing resistance to the antibiotics currently available and so there is ever a need to develop more ~-lactam antibiotics, which are effective and yet safe. A major drawback to the ~-lactams is the degree of immunologically adverse reactions they induce. It was the aim of this study to develop both mechanistic and immunological methods to enable the prediction of a B-lactam's potential to induce an allergic response and to determine if a relationship between these responses and the molecular properties of the ~-lactams was present. In this study a database pertaining to frequency by which 70 p-lactams induce adverse reactions has been compiled and used to produce 27 QSAR models. A highly sensitive assay for the quantitation of cross-reactivity between B-lactams and serum anti-benzylpenicillin antibodies has been developed and used to determine the cross-reactivity potential of 31 ~-lactams and to develop 18 QSAR models. All of the QSARs developed suggest that the shape and electron separation of the ~-lactams are crucial to the development and extent of adverse response or crossreactivity induced by a specific p-lactam antibiotic, new or old. The QSARs developed will enable the design and development of new ~-lactam antibiotics which present a significantly lower risk of inducing immunologically mediated adverse responses when used therapeutically. Two sensitive assays for the quantitative detennination of the cytokines IL2 and IL4 in lymphocyte culture supernatants have been developed, and have been shown to have a potential use in the prediction of the type of immunological response initiated following p-Iactam stimulation of a sensitised individual.

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Thomsen, Marianne. "QSARs in environmental risk assessment : interpretation and validation of SAR/QSAR based on multivariate data analysis /." Roskilde : Roskilde University, Department of Life Science and Chemistry, 2001. http://hdl.handle.net/1800/538.

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Ishiki, Hamilton Mitsugu. "Relações quantitativas entre estrutura química e atividade biológica (QSAR/QSAR-3D) de compostos com potencial atividade antituberculose." Universidade de São Paulo, 2005. http://www.teses.usp.br/teses/disponiveis/46/46135/tde-25042016-172925/.

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A tuberculose (TB) é uma doença causada pelo Mycobacterium tuberculosis. De acordo com estimativas da Organização Mundial da Saúde, a tuberculose é responsável pela morte de ~2 a 3 milhões de pessoas/ano no mundo e nos próximos 15 anos cerca de 1 bilhão de pessoas deverão ser infectadas, e destas, aproximadamente 35 milhões deverão morrer. Apesar de existirem vários medicamentos sendo utilizados no tratamento da doença, constatasse o crescimento no número de casos devido, principalmente, às variedades resistentes do M. tuberculosis. Considerando-se o aparecimento de cepas resistentes em TB, recomenda-se que novos medicamentos e/ou alvos biológicos alternativos devam ser intensivamente pesquisados. A ribonucleotídeo redutase (RNR), por exemplo, é uma proteína de interesse, pois catalisa uma etapa importante e única na síntese de novo dos dNTPs, reduzindo o ribonucleosídeo 5\' -difosfato ao seu correspondente desoxirribonucleosídeo 5\' -difosfato. A RNR é importante na síntese do DNA, e portanto, na divisão das células. Esta enzima importante, que possuí 16% de homologia com a RNR de mamíferos, é um alvo potencial para o desenvolvimento de novos fármacos, com provável aplicação no tratamento do câncer, da malária e do tripanossoma. Sabe-se que diferentes classes de compostos, através de diferentes mecanismos de ação, inibem a RNR, incluindo as α-(N)-heterocíclicas carboxaldeído tiossemicarbazonas, um dos inibidores mais potentes da RNR. Sabe-se que alguns derivados da tiossemicarbazona, inibidoras da RNR de células tumorais, apresentam atividade frente o M. tuberculosis atuando provavelmente através do mesmo mecanismo, envolvendo a inibição da correspondente RNR. Neste contexto, nesta tese de doutorado, foram aplicadas diferentes abordagens de QSAR/QSAR-3D no estudo de 40 derivados da 2-piridino-carboxaldeído tiossemicarbazona, inibidores da RNR de células H.Ep.-2, retirados de literatura selecionada (French & Blanz-Jr. 1974). Estes compostos foram divididos em cinco séries, a saber: séries A, B, C, D, e E contendo, respectivamente, 40, 39, 30, 23 e 22 compostos, na tentativa de tornar estas séries estruturalmente mais homogêneas. Para cada série, foram criados três grupos de treinamento e os respectivos grupos de teste (I, II e III), visando-se avaliar o poder de predição dos modelos gerados através das análises de QSAR/QSAR-3D. Para as análises de QSAR clássico, foram utilizados como variáveis independentes, os descritores mais relevantes gerados através do programa DRAGON e, pré-selecionados por PLS. Considerando-se a ausência de informações sobre a estrutura cristalográfica da enzima RNR do M. tuberculosis, os estudos de QSAR-3D foram iniciados empregando-se metodologias propostas em CoMFA e, em CoMSIA, implementadas no programa SYBYL. Além destas, foi realizada a modelagem por homologia da RNR do M. tuberculosis, utilizando-se o programa WHATIF. Para as abordagens CoMFA e CoMSIA as geometrias otimizadas através do método semi-empírico AM1 foram alinhadas átomo-a-átomo e, através da similaridade dos respectivos campos estéricos e eletrostáticos, utilizando-se o programa SEAL. Nos dois procedimentos a geometria do composto não substituído, um dos mais ativos na série, foi utilizada como molde considerando-se a ausência de informações sobre a conformação bioativa. A modelagem da RNR por homologia foi realizada utilizando-se como molde as estruturas cristalográficas, respectivamente, do C. ammoniagenes (código PDB 1KGN) e da S. typhimurium (código PDB 1R2F), sambas apresentando valores de identidade superior a 65%. Mais recentemente foram publicados os dados cristalográficos para a cadeia beta (subunidade menor) da RNR do M. tuberculosis (código PDB 1UZR). Os modelos CoMFA e CoMSIA gerados apresentaram valores aceitáveis para os coeficientes de correlação de predição, com altos valores para os coeficientes de correlação ajustados e baixos valores para os erros padrões. Os melhores modelos CoMFA e CoMSIA foram obtidos considerando o grupo com substituintes apenas na posição 5 do anel piridínico. Razoáveis coeficientes de correlação de predição para os modelos CoMSIA com altos coeficientes de correlação de ajuste e baixos valores para os erros padrões forma obtidos. Os mapas de contorno gerados em CoMFA e CoMSIA sugerem que grupos aceptores de ligações de hidrogênio próximos ao nitrogênio do anel piridínico deverá aumentar o valor da atividade inibitória. Esta observação está em boa concordância com os dados da literatura, na qual a formação de um complexo entre a TSC e o íon Ferro foi sugerido para a inibição da RNR. Estes estudos deverão permitir um melhor entendimento sobre as características estruturais desta classe de TSC inibidoras da RNR, como agentes antitumorais, em termos dos campos estéricos, eletrostáticos, hidrofóbico, doador e aceptor de ligações de hidrogênio, bem como a contribuição para o desenvolvimento racional de novos inibidores para esta importante enzima. Adicionalmente, dois compostos preparados em nosso laboratório, demonstraram atividade frente o M. tuberculosis, em testes realizados in vivo.
Tuberculosis is an illness caused by Mycobacterium tuberculosis. Data from World Health Organization (WHO) estimates, that about 2-3 millions of human population died by Mycobacterium tuberculosis infection and that during the next 15 years about 1 billion will be infected and 35 million will certainly die. Although, in the clinic it was found several antiTBdrugs, these numbers will increase due several reasons including M. tuberculosis resistant strains. It has been stressed the importance of novel medicines and/or alternative biological targets research projects. It is known that Ribonucleotide reductase (RNR), is an enzyme that catalyses the rate limiting step in the de novo synthesis of dNTPs, reducing the ribonucleoside 5\'-diphosphates to the corresponding deoxyribonuc1eoside 5\' -diphosphates. RNR has a critical role in the DNA synthesis and, hence, cell division. This key enzyme, that shows 16% homology when compared with mammals RNR, is a potential target for drug design of cell growth inhibitors, with potential application in cancer therapy, antimalaria and trypanosome chemotherapy. It is known that different types of compounds or species by means of different mechanism pathways can show RNR inhibition, including α-(N)-heterocyclic carboxaldehydes thiosemicarbazones that are one of the most potent classes of RNR inhibitors. More than that, some of them, that shows activity against M. tuberculosis seems to follow the same mechanism pathways proposed to the thiosemicarbazones tumor cells activity that means, that they probably are RNR inhibitors. In this study, a series of 40 α-(N)-2-formyl-pyridine thiosemicarbazone derivatives tested against RNR of H.ep.-2-cells (human epidermoid carcinoma), taken from selected literature (French & Blanz-Jr. 1974), has quantitatively analyzed by means of several QSAR/3D-QSAR approaches. These compounds were divided into 5 individual subsets, namely A, B, C, D, and E, having 40, 39, 30, 23 e 22 compounds, respectively. This procedure has been done in order to achieve more structurally homogeneous subsets. For each set, three individual training and test sets (I,II and III) have been created in order to evaluate the predictivity power of the generated QSAR/3D-QSAR models. QSAR analysis have been done using descriptors generated by DRAGON program that have been further pre-selected by PLS procedures. Considering that crystallographic data of RNR M. tuberculosis are not available in the literature, 3D-QSAR studies have been done these applying, initially, CoMFA and CoMSIA approaches, implemented in SYBYL. Homology model studies have been performed with WHATIF program CoMFA e CoMSIA approaches used optimized geometry obtained by semi-empirical AM1 methods that have been aligned by two different methods. Rigid alignment, in which the compounds were fitted atom-by-atom onto a template, based on the root mean square fit. The N(l) and C(2) atoms of the pyridine moiety and the heavy atoms of thiosemicarbazone backbone of TSC were used as template structure. (2) Field based, in which the steric and electrostatic fields, generated by the SEAL program were considered in the alignment. In both procedures the unsubstituted 2-formylpyridine thiosemicarbazone in its syn conformation, has been taken as template. Homology RNR models were done using as template crystallographic data of ammoniagenes (1KGN) and S. typhimurium (1R2F) as template, respectively, with identity larger than 65%. More recent1y new crystallographic data have been published for the beta chain (smaller subunity) of RNR do M. tuberculosis (1UZR). CoMFA and CoMSIA generated models showed acceptable predictive correlation coefficients with high fitted correlation coefficients and low standard errors. Betler CoMFA and CoMSIA models have been derived considering a homogeneous subset of TSC substituted only at 5-position in pyridine ring. Reasonable predictive correlation coefficients for CoMSIA models with high fitted correlation coefficients and very low standard errors were obtained. The derived CoMFA and CoMSIA countour maps suggested that a hydrogen bond acceptor near the nitrogen pyridine ring could enhance inhibitory activity value. This observation is in good agreement with literature, in which a complex formation between TSC and iron ion has been suggested, to RNR inhibition. These studies are expected to enhance the understanding of the structural features of this class of TSC-RNR inhibitors as antitumor agents in terms of steric, electrostatic, hydrophobic and hydrogen donor and acceptor fields as well as to contribute to rational design of inhibitors of this key enzyme. Additionally, two compounds that have been prepared by us showed activity against M. tuberculosis using in vivo test system.

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12

Ruggiu, Fiorella. "Property-enriched fragment descriptors for adaptive QSAR." Thesis, Strasbourg, 2014. http://www.theses.fr/2014STRAF037/document.

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Les descripteurs ISIDA enrichis par propriété ont été introduit pour encoder les structures moléculaires en chémoinformatique en tant que nombre d’occurrence de sous-graphes moléculaires spécifiques dont les sommets représentant les atomes sont colorés par des propriétés locales tel que les pharmacophores dépendant du pH, les identifiants de champs de force, les charges partielles, les incréments LogP ou les propriétés extraites d’un modèle QSAR. Ces descripteurs, par leurs large choix d’option, permettent à l’utilisateur de les adapter au problème à modéliser. Ils ont été utilisés avec succès dans une étude de criblage virtuel sur des inhibiteurs de protéases et plusieurs modèles QSAR sur le coefficient de partage octanol-eau, l’index d’hydrophobicité chromatographique, l’inhibition du canal hERG, la constante de dissociation acide, la force des accepteurs de liaison hydrogène et l’affinité de liaison des GPCR
ISIDA property-enriched fragment descriptors were introduced as a general framework to numerically encode molecular structures in chemoinformatics, as counts of specific subgraphs in which atom vertices are coloured with respect to a local property - notably pH-dependent pharmacophore, force field, partial charges, logP increments and QSAR model extracted properties. The descriptors leave the user a vast choice in terms of the level of resolution at which chemical information is extracted into the descriptors to adapt them to the problem. They were successfully tested in neighbourhood behaviour and QSAR modelling challenges, with very promising results. They showed excellent results in similarity-based virtual screening for analogue protease inhibitors, and generated highly predictive octanol-water partition coefficient, chromatographic hydrophobicity index, hERG channel inhibition, acidic dissociation constant, hydrogen-bond acceptor strength and GPCR binding affinity models

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Oliveira, Kesley Moraes Godinho de. "Estudos Qsar de compostos com atividade leishmanicida." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/249746.

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Orientadores: Yuji Takahata, Rogerio Custodio
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Quimica
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Resumo: O objeto de estudo desta tese é a forma mais severa e letal de Leishmaniose: a Leishmaniose Visceral, LV, cujo principal agente etiológico é a espécie Leishmania donovani. O objetivo deste trabalho é o desenvolvimento de modelos Quantitativos das Relações Estrutura-Atividade para duas séries de compostos com atividade antileishmaniose contra formas amastigotas de Leishmania donovani. A primeira série envolve vinte e um análogos de nucleosídeos pirazolo-pirimidínicos e a segunda série compreende oito antifúngicos. Para garantir a robustez dos modelos, além dos compostos que compõem as respectivas séries, foram selecionadas moléculas com conhecida atividade contra LV para compor um conjunto de teste e avaliar a capacidade de previsão dos respectivos modelos. Para a série dos nucleosídeos foram desenvolvidos modelos de regressão logística e árvore de classificação. Em ambas as abordagens os descritores Mor26v e o GAP(HOMO, HOMO-1) se mostraram relevantes para a explicação da atividade leishmanicida destes compostos. O modelo de regressão logística atingiu 90,5% para acurácia de classificação para o conjunto de trabalho e 58% para o conjunto de teste após a análise do domínio de aplicabilidade do modelo. O modelo para árvore de classificação alcançou 95% para acurácia de classificação para o conjunto de trabalho e 83% para o conjunto de teste. Para a série dos antifúngicos foi utilizado um modelo de regressão linear múltipla onde a energia eletrônica e a área da superfície polar se mostraram importantes para a atividade leishmanicida da série. Os valores previstos exibem 98% de correlação com os valores experimentais. Os valores encontrados para o conjunto de teste também estão de acordo com a literatura. Finalmente, novos compostos foram propostos para síntese e avaliação da atividade leishmanicida.
Abstract: The object of study of this thesis is the most severe and lethal form of leishmaniasis: visceral leishmaniasis, LV, whose main etiological agent is the species Leishmania donovani. The goal of this work is the development of Quantitative Structure-Activity Relationship models for two series of compounds presenting antileishmanial activity against amastigotes of Leishmania donovani. The first series includes twenty-one analogues of pyrazolo-pyrimidine nucleosides and the second series comprises eight antifungals. To ensure the robustness of the models, in addition to the compounds that make up their series, molecules with known activity against LV were selected to compose a testset and evaluate the predictive power of their models. For the series of nucleosides logistic regression models and tree classification were developed. In both approaches, the Mor26v and GAP(HOMO, HOMO-1) descriptors were relevant to explain the leishmanicidal activity of these compounds. The logistic regression model reached 90.5% for classification accuracy to the workingset and 58% for testset after analysis of the domain of applicability of the model. The classification tree model reached 95% for classification accuracy of the workingset and 86% for the testset. A multiple linear regression model was applied to the series of antifungal agents. The electron energy and polar surface area were important for the leishmanicidal activity of this series. The predicted values showed 98% of correlation with the experimental values. The values found for the testset are also in agreement with the literature. Finally, new compounds were proposed for synthesis and evaluation of leishmanicidal activity.
Doutorado
Físico-Química
Doutor em Ciências

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MANSOURI, KAMEL. "New molecular descriptors for estimating degradation and fate of organic pollutants by QSAR/QSPR models within reach." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/45611.

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Organic pollutants that resist degradation in the environment can accumulate in body tissues and cause unavoidable intoxications to organisms in wild life as well as humans. The possible effects, usually increasing with the cumulative exposure to such chemicals, are not always addressed adequately in risk assessment procedures evaluating long and short-term contact hazard. Thus, chemicals accumulation, degradation and environmental fate are of prime concern for REACH when defining side effects due to chronic exposure. Characteristics and behavior of organic pollutants have been investigated experimentally during the last decades by use of various methods of trace analysis. However, the available data still contains several gaps. In this aim, REACH promotes the use of alternative methods to reduce the number of animal tests and suggests in-silico methods such as Quantitative Structure-Activity Relationships (QSARs) to fill the lack of knowledge. The goal of this thesis, in the framework of the ECO-ITN project, was to build QSAR models with high reliability based on good experimental data for optimal estimation of environmental endpoints of interest for REACH. New molecular descriptors and feature selection techniques have been tested paying particular attention to the validation steps and applicability domain definition.

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SAHIGARA, FAIZAN ABDULRAZAK. "Tools for prediction of environmental properties of chemiclas by QSAR/QSPR within reach. An applicability domain perspective." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/46045.

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As the title suggests, this work is mainly focussed at providing an Applicability Domain (AD) perspective towards the QSAR/QSPR models predicting environmental properties relevant to REACH regulations. A well defined AD is one of the prerequisites for a predictive model before it is considered as validated for regulatory purposes. The main idea behind compiling this thesis is to provide the reader with all the major insights towards defining a model’s AD where it can reliably predict the modelled endpoint for new test samples.

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Brust, Kristin. "Toxicity of aliphatic amines on the embryos of zebrafish Danio rerio - experimental studies and QSAR: experimental studies and QSAR." Doctoral thesis, Technische Universität Dresden, 2001. https://tud.qucosa.de/id/qucosa%3A24160.

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The toxicity of 36 aliphatic amines on the embryos of the zebrafish Danio rerio were investigated. The DarT (Danio rerio Toxicity assay) was used to determine the lethal concentrations within a 48 h static acute toxicity test. A QSAR (Quantitative Structure-Activity Relationship) was performed using the LC50 values and molecular descriptors such as lipophilicity, maximum positive charge on hydrogen atom and the effective diameter of the molecule. In general, the toxicity of primary and secondary amines could be described by the lipophilicity as descriptor. The toxicity of the tertiary amines tested could be only described by a bilinear regression model. Further, regression models for other aquatic species such as the fathead minnow Pimephales promelas, Daphnia magna and Tetrahymena pyriformis showed that the toxicity of each species is a good predictor for each other.

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Hodges, Geoffrey. "QSAR studies of surfactant toxicity to Daphnia magna." Thesis, Liverpool John Moores University, 1997. http://researchonline.ljmu.ac.uk/4910/.

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The inherent nature of surfactants to aggregate at surfaces makes measurement of log P (octanoll water partition coefficient) for these substances extremely difficult. It is possible, however, to calculate a log P descriptor based on the method described by Hansch and Leo (1979). Work presented in this thesis describes the study of the acute toxicity of sulphonated esters (FAES) of general formula R-CH(S03"Na +)-C02-R' to Daphnia magna. Due to structural similarities of this class of anionic surfactant to linear alkylbenzene sulphonate (LAS), it was considered that the log P based QSAR originally developed to describe the toxicity of LAS to D. magna (Roberts, 1989) also would be a good predictor of the acute toxicity for FAES substances. Results of the toxicity studies showed that FAES substances were less toxic than predicted. However, when plotted against log P' Calculated using the conventional fragment approach of Hansch and Leo with the addition of a position dependent branching factor (PDBF) to account for water sharing between hydrocarbon chains, the regression slope was para"el to but distinct from that of LAS. This indicated that either FAES substances were not acting as by the same mode of action as LAS or that modification of the log P calculation was required. Further studies of the toxicity of binary mixtures of FAES with known polar and non-polar narcotics, established that FAES exhibited concentration addition with LAS and phenol. This indicated that they behaved with a similar mode of action and it would be expected that LAS and FAES would share the same QSAR. The difference of the regression slopes of FAES and LAS observed? earlier, therefore, suggested the requirement of a modification to the original log P calculation. The modified proximity factor developed in this thesis considers the effects of relative size of proximal polar fragments on log P.? Spherical hydration sheaths surrounding each fragment were assumed and 'overlapping volumes calculated for fragments at different carbon separation. When incorporated into the log P calculation, the new log P values now allow toxicity values for LAS and F AES substances to be incorporated into the same QSAR.

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Dimitriadis, Spyridon. "Multi-task regression QSAR/QSPR prediction utilizing text-based Transformer Neural Network and single-task using feature-based models." Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177186.

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With the recent advantages of machine learning in cheminformatics, the drug discovery process has been accelerated; providing a high impact in the field of medicine and public health. Molecular property and activity prediction are key elements in the early stages of drug discovery by helping prioritize the experiments and reduce the experimental work. In this thesis, a novel approach for multi-task regression using a text-based Transformer model is introduced and thoroughly explored for training on a number of properties or activities simultaneously. This multi-task regression with Transformer based model is inspired by the field of Natural Language Processing (NLP) which uses prefix tokens to distinguish between each task. In order to investigate our architecture two data categories are used; 133 biological activities from ExCAPE database and three physical chemistry properties from MoleculeNet benchmark datasets. The Transformer model consists of the embedding layer with positional encoding, a number of encoder layers, and a Feedforward Neural Network (FNN) to turn it into a regression problem. The molecules are represented as a string of characters using the Simplified Molecular-Input Line-Entry System (SMILES) which is a ’chemistry language’ with its own syntax. In addition, the effect of Transfer Learning is explored by experimenting with two pretrained Transformer models, pretrained on 1.5 million and on 100 million molecules. The text-base Transformer models are compared with a feature-based Support Vector Regression (SVR) with the Tanimoto kernel where the input molecules are encoded as Extended Connectivity Fingerprint (ECFP), which are calculated features. The results have shown that Transfer Learning is crucial for improving the performance on both property and activity predictions. On bioactivity tasks, the larger pretrained Transformer on 100 million molecules achieved comparable performance to the feature-based SVR model; however, overall SVR performed better on the majority of the bioactivity tasks. On the other hand, on physicochemistry property tasks, the larger pretrained Transformer outperformed SVR on all three tasks. Concluding, the multi-task regression architecture with the prefix token had comparable performance with the traditional feature-based approach on predicting different molecular properties or activities. Lastly, using the larger pretrained models trained on a wide chemical space can play a key role in improving the performance of Transformer models on these tasks.

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Cramer, Bruno. "Estudos de QSAR-2D aplicados a diterpenóides clerodanos e dibenzoilidrazinas." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/249743.

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Orientador: Yuji Takahata
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química
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Resumo: A tese foi organizada em forma de cinco estudos de caso de QSAR-2D, usando compostos da literatura. Foram utilizados diterpenóides clerodanos e N,N¿- dibenzoil-N-t-butilidrazinas (DBHs) para desenvolver modelos de QSAR, propondo o uso de uma metodologia que emprega análise conformacional. Os modelos de QSAR são construídos pela escolha do confôrmero que melhor reproduz a bioatividade. O critério de seleção dos confôrmeros é orientado pelo resíduo entre valor observado e o predito. O método proposto aumenta a qualidade de predição interna, auxilia a análise de outliers, e em casos específicos, pode proporcionar melhor interpretabilidade do comportamento de descritores em relação à atividade biológica. Após validação interna e externa, os modelos de QSAR foram empregados para simular a proposta de novos compostos. Duas metodologias independentes de regressão foram usadas, Regressão Linear Múltipla (MLR) e Máquinas de Vetores de Suporte (SVM), objetivando produzir modelos de QSAR equivalentes, ambos produzindo resultados próximos de predição no conjunto de treinamento, auxiliando na análise e seleção de resultados preditos de novos compostos, aumentando a confiabilidade e robustez dos modelos de QSAR. Foram propostos novos diterpenóides clerodanos derivados de produtos naturais (n = 113) e outros 53 propostos in silico contra células V79. Novas dibenzoilidrazinas propostas in silico tiveram sua atividade inseticida e larvicida predita para novos bioensaios contra Spodoptera exigua (n = 13) e S. frugiperda (n = 30). Através do estudo de homologia a tese contribui com o domínio ligante do receptor ecdisona de S. exigua (SeEcR-LBD). Empregando docking, informações foram obtidas sobre as possíveis interações das DBHs com os aminoácidos, uma contribuição na literatura pertinente. DBHs halogenadas foram analisadas identificando a provável interação dos halogênios com os aminoácidos no domínio ligante do receptor ecdisona de Heliothis virescens (HvEcR-LBD), análise estendida a S. exigua (SeEcR-LBD).
Abstract: The thesis was organized in the form of five 2D-QSAR case studies using compounds from literature. Clerodan diterpenoids and N, N¿-dibenzoy-N-tbutylhydrazines (DBHs) were used to develop predictive QSAR models proposing a methodology that uses conformational analysis. QSAR models are built by choosing the conformer that best reproduces the experimental bioactivity. The conformer selection is oriented on a residual criterion between observed and predicted values. The proposed method increases the quality of internal prediction, aids the analysis of outliers, and in specific cases, may provide better interpretability of the descriptor behavior in relation to the bioactivity. After internal and external validation, the QSAR models were used to simulate the proposition of new compounds. Two independent regression methodologies, Multiple Linear Regression (MLR) and Support Vector Machine (SVM) were used to produce equivalent QSARs, both producing close predicted results of the training set and aiding in the analysis and selectivity of MLR-SVM QSARs predicted results of new compounds, increasing the reliability and robustness of the QSAR models. New clerodan diterpenoids derived from natural products (n = 113) and another 53 in silico proposed, have their bioactivity predicted against V79 cells. New in silico dibenzoylhydrazines against Spodoptera exigua (n = 13) and S. frugiperda (n = 30) have their insecticidal and larvicidal activity predicted and proposed for new bioassays. Through homology study the thesis contributes with the S. exigua ecdyson receptor ligand-binding domain (SeEcR-LBD). Using docking, information was obtained about possible interactions of DBHs with amino acids, a contribution to the entailed literature. Halogen substituted DBHs were analyzed identifying their probable interaction with amino acids of Heliothis virescens ecdyson receptor ligand binding domain (HvEcR-LBD), analysis extended to S. exigua (SeEcR-LBD)
Doutorado
Físico-Química
Doutor em Ciências

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Garcia, Mariana Lopes. "Estudos computacionais da enzima N-miristoiltransferase de Plasmodium falciparum e seus inibidores como candidatos a agentes antimaláricos." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/76/76132/tde-15092017-084415/.

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A malária é uma doença infecciosa causada pelos parasitas do gênero Plasmodium e transmitida pelo mosquito Anopheles spp. Devido ao surgimento de casos de resistência aos fármacos disponíveis novos alvos e candidatos a fármacos são necessários. Recentemente, a enzima N-miristoiltransferase (NMT) foi confirmada como essencial para o parasita e validada como alvo terapêutico para o desenvolvimento de candidatos a fármacos antimaláricos. O objetivo desse trabalho foi identificar os determinantes moleculares responsáveis pela atividade inibitória de uma série de derivados benzotiofênicos frente à NMT. Nesse sentido, estudos de relação quantitativa estrutura-atividade (QSAR) 2D e 3D foram desenvolvidos para dois conjuntos de dados de derivados benzotiofênicos como inibidores da enzima do parasita (PfNMT) e a homóloga humana (HsNMT). Além disso, estudos de modelagem por homologia da PfNMT foram conduzidos. Os estudos de QSAR 2D foram desenvolvidos pelo método de Holograma QSAR (HQSAR). O modelo estrutural de PfNMT foi aplicado na construção dos modelos QSAR 3D CoMFA (Comparative Molecular Field Analysis) e CoMSIA (Comparative Molecular Similarity Index Analysis). Os estudos de QSAR 3D foram conduzidos com diferentes métodos de cálculo de carga parcial atômica (Gasteiger-Hückel, MMFF94 e AM1-BCC, CHELPG e Mulliken) e de alinhamento molecular (Máxima Subestrutura Comum, alinhamento flexível e baseada no alvo molecular). Os melhores modelos construídos pelos métodos de QSAR 2D e 3D foram robustos, internamente consistentes e com elevada capacidade de predição da atividade de novos compostos contra a PfNMT. Os mapas de contribuição e de contorno geraram informações importantes sobre a relação estrutura-atividade dos compostos. Os resultados permitiram a identificação das bases moleculares responsáveis pela atividade dos inibidores benzotiofênicos e são úteis para o planejamento de novos inibidores mais potentes e seletivos para a enzima do parasita.
Malaria is an infectious disease caused by protozoan parasites of the genus Plasmodium and transmitted by Anopheles spp. mosquitos. Due to the emerging resistance to current available drugs, great efforts for new molecular target and drugs are required. Recently, N-myristoyltransferase (NMT) was confirmed as an essential enzyme to malaria parasites and validated as a chemically tractable target for the development of new drug candidates against malaria. This work aimed to shed light on the molecular requirements underlying the inhibitory activity of benzothiophene derivatives against NMT. Therefore, 2D and 3D quantitative structure-activity relationship (QSAR) studies were developed for two datasets of benzothiophene derivatives as P. falciparum NMT (PfNMT) and the human homologue (HsNMT) inhibitors. Also, homology modeling studies for PfNMT were developed. The 2D QSAR studies were developed by the Hologram QSAR (HQSAR) method. The PfNMT structural model was applied in the construction of 3D QSAR models CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Index Analysis). Different molecular alignment (maximum common substructure, flexible alignment and structure based) and atomic partial charge calculation (Gasteiger-Hückel, MMFF94, AM1-BCC, CHELPG and Mulliken) methods were used to build the 3D QSAR models. The best models showed internal consistency and high predictive ability of biological activity against PfNMT. The contribution and contour maps gave important information about compounds structure-activity relationship. The results allowed the identification of the molecular requirements underlying the inhibitory activity and should be useful for the design of novel potent and selective PfNMT inhibitors as antimalarial drug candidates.

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Pereira, Estevão Bombonato. "Estudo da relação quantitativa estrutura-atividade de compostos β-carbolínicos, substituídos nas posições 1 e 3, utilizados no tratamento de câncer de pulmão e melanoma cutâneo." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/75/75134/tde-09062014-162046/.

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O câncer é uma doença que aflige pessoas no mundo todo, e mata muitas todos os anos. Muitos estudos são desenvolvidos para sintetizar novos compostos com atividade antitumoral cada vez melhor. O maior número de compostos possibilita um maior número de possibilidades de cura, já que alguns tumores podem adquirir resistência ao medicamento, sendo necessária a troca por outro.
Para que não seja feita uma síntese aleatória de compostos, desperdiçando tempo, reagentes e dinheiro sintetizando compostos inativos, um estudo teórico prévio para orientar a síntese é válido. Um estudo QSAR pode orientar a síntese indicando quais compostos são mais interessantes de serem sintetizados e quais são menos interessantes. Assim, há o desenvolvimento de mais compostos ativos em um menor tempo, do que se fosse realizada sínteses e testes para todos os compostos possíveis.
O presente estudo tem esse foco, avaliar a relação quantitativa entre a estrutura molecular e a atividade antitumoral de compostos β-carbolínicos substituídos nas posições 1 e 3. Nesse estudo será possível elucidar quais características são relevantes para que os compostos sejam ativos no tratamento de câncer de pulmão e melanoma.
Cancer is a disease that afflicts people worldwide and kills many every year. Many studies are developed to synthesize new compounds with better antitumor activity. The largest number of compounds allows a greater number of curability, because some tumors may acquire used drug resistance and are necessary different drugs.
To avoid a random synthesis of compounds, wasting time, money and reagents in synthesizing inactive compounds, a previous theoretical study as guide of synthesis is valid. A QSAR study can guide the synthesis indicating which compounds are most interesting to be synthesized and which are less interesting. Thus, more compounds active are developed in a shorter time.
The present study has this focus, assess the quantitative relationship between molecular structure and antitumor activity of β-carboline compounds substituted in positions 1 and 3. In this study will be possible to elucidate characteristics that are relevant to the compounds under study be active in the treatment of lung cancer and melanoma.

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Ye, Lin Holder Andrew J. "Application of quantum mechanical QSAR to dental molecule design." Diss., UMK access, 2007.

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Thesis (Ph. D.)--Dept. of Chemistry and School of Pharmacy. University of Missouri--Kansas City, 2007.
"A dissertation in chemistry and pharmaceutical science." Advisor: Andrew J. Holder. Typescript. Vita. Description based on contents viewed Apr. 15, 2008; title from "catalog record" of the print edition. Includes bibliographical references (leaves 89-93). Online version of the print edition.

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Hobocienski, Bryan Christopher. "Locality-Dependent Training and Descriptor Sets for QSAR Modeling." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1577716259011585.

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Barbosa, Euzébio Guimarães. "Ferramentas para QSAR-4D dependente de receptores = aplicação em uma série de inibidores da tripanotiona redutase do T. cruzi." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/248547.

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Orientador: Márcia Miguel Castro Ferreira
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química
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Resumo: LQTA-QSAR é uma metodologia computacional para QSAR-4D desenvolvida pelo Laboratório de Quimiometria Teórica e Aplicada implementada em um software de acesso livre. O método permite considerar simultaneamente as vantagens da representação molecular multiconformacional e os descritores de campos de interação. Esta tese apresenta a evolução da proposta inicial da metodologia LQTA-QSAR independente de receptores para uma abordagem dependente de receptores. Sua aplicação é demonstrada na construção de modelos de QSAR-4D para a previsão da atividade inibitória de compostos fenotiazínicos da enzima tripanotiona redutase. Foi obtido um modelo com bom poder de previsão (Qprev = 0,78) e com descritores de fácil interpretação. Tal modelo pode ser usado para a proposição de compostos que poderão vir a ser usados para o tratamento da doença de chagas. Para a filtragem e seleção de descritores foi necessário o desenvolvimento de um protocolo completamente distinto daquele disponível na literatura. Foi proposto um procedimento automatizado para identificar e eliminar descritores irrelevantes quando a correlação e um algoritmo que elimina descritores com distribuição díspar em relação à atividade biológica. Foram introduzidos também testes de validação de modelos QSAR nunca antes usados para modelos que utilizam descritores de campo de interação. O protocolo completo foi testado em três conjuntos de dados e os modelos obtidos tiveram capacidade de previsão superior aos da literatura. Os modelos mostraram ser bastante simples e robustos quando submetidos aos testes leave-N-out e y-randomization
Abstract: The New Receptor-Dependent LQTA-QSAR approach is proposed as a new 4D-QSAR method. The RD-LQTA-QSAR is an evolution to the receptor independent LQTA-QSAR. This approach make use of the simulation package GROMACS to carry out molecular dynamics simulations and generate a conformational ensemble profile for each compound. Such ensemble is used to build molecular interaction field based QSAR models, as in CoMFA. To verify the usefulness of the methodology it was chosen some phenothiazine derivatives that are specific competitive T. cruzi trypanothione reductase inhibitors. Using a combination of molecular docking and molecular dynamics simulations the binding mode of 38 phenotiazine derivatives was evaluated in a simulated induced fit approach. The ligands¿ alignment, necessary to the methodology, was performed using both ligand and binding site atoms hereafter enabling unbiased alignment. The obtained models were extensively validated by Leave-N-out cross-validation and y-randomization techniques to test robustness and absence of chance correlation. The final model presented Q LOO of 0.87 and R of 0.92 and suitable external prediction = 0.78. It is possible to use the obtained adapted binding site of to perform virtual screening and ligand structures based design, as well as using models descriptors to design new inhibitors. In the process of QSAR modeling, the relevance of correlation and distribution profiles were tested in order to improve prediction power. A set of tools to filter descriptors prior to variable selection and a protocol for molecular interaction field descriptors selection and models validation are proposed. The algorithms and protocols presents are quite simple to apply and enable a different and powerful way to build LQTA-QSAR models
Doutorado
Físico-Química
Doutor em Ciências

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Weber, Karen Cacilda. "Modelagem molecular de compostos arilpiperazínicos e suas interações com o receptor 5-HT1A." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/75/75131/tde-05122008-165529/.

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Os inibidores seletivos da recaptação de serotonina (ISRSs) representam a classe mais importante de antidepressivos em uso clínico atualmente. Entretanto, esses medicamentos costumam levar de duas a seis semanas para apresentar os efeitos de sua ação terapêutica. Estudos clínicos mostram que quando um antagonista do receptor 5-HT1A é administrado juntamente com um ISRS, um aumento da concentração extracelular de serotonina é observado nas áreas terminais dos neurônios. Assim, a combinação de um antagonista do receptor 5-HT1A com um ISRS pode acelerar o início da ação antidepressiva, aumentando a eficácia do tratamento farmacológico da depressão. A classe mais importante de ligantes do receptor 5-HT1A são os compostos arilpiperazínicos. O presente estudo teve como objetivo o entendimento das características importantes para as interações entre uma série de compostos arilpiperazínicos com o receptor 5-HT1A. Para tal, foram realizados estudos de Relação Quantitativa entre Estrutura e Atividade (QSAR) bi- e tridimensionais, empregando as seguintes abordagens: métodos quimiométricos baseados em descritores teóricos, QSAR por hologramas (HQSAR) e o método de Análise Comparativa de Campos Moleculares (CoMFA). Essas análises foram complementadas com a modelagem por homologia do receptor 5-HT1A e com estudos de docking ligante-receptor realizados para alguns compostos arilpiperazínicos. Modelos de QSAR com boa consistência interna, habilidade preditiva e estabilidade foram obtidos em todos os casos. Os modos de interação observados apresentaram consistência com dados experimentais disponíveis sobre os resíduos importantes para as interações com ligantes arilpiperazínicos. Os principais resultados indicaram algumas características dos ligantes que são importantes para a afinidade pelo receptor 5-HT1A, tais como a presença de um anel benzotiofeno como substituinte Ar2, substituintes pouco volumosos na posição Z e receptores de ligações de hidrogênio na posição orto do anel Ar1. Esses resultados foram corroborados pelo estudo das interações com o modelo do receptor 5-HT1A, que indicou uma importante interação hidrofóbica do grupo benzotiofeno com o resíduo Trp6.48 do receptor, assim como uma ligação de hidrogênio entre a hidroxila na posição Z e o resíduo Thr3.37 e, ainda, entre o oxigênio do anel Ar1 e o resíduo Asn7.39. As informações obtidas neste estudo podem fornecer subsídios para o planejamento de novos ligantes com afinidade pelo receptor 5-HT1A.
Selective serotonin reuptake inhibitors (SSRIs) are the most important class of antidepressants in current clinical use. However, they present the serious drawback of a delay of two to six weeks in the onset of therapeutic effect. Clinical studies have shown that when a 5-HT1A receptor antagonist is administrated along with a SSRI, an increase of extracellular serotonin concentration in neuronal terminal areas is observed. Thus, the combination of a 5- HT1A receptor antagonist and a SSRI could accelerate the onset of antidepressant action, improving the pharmacological treatment of depression. The most important class of 5-HT1A receptor ligands are arylpiperazine compounds. In the present study, our aim was to understand the main features of the interaction between a series of arylpiperazines and the 5- HT1A receptor. Bi- and Tridimensional Quantitative Structure-Activity Relationship (QSAR) studies were conducted employing the following approaches: chemometric methods based on theoretical descriptors, Hologram QSAR (HQSAR), and Comparative Molecular Field Analysis (CoMFA). These analyses were complemented by 5-HT1A receptor homology modeling and ligand-receptor docking studies. QSAR models presenting good internal consistency, predictive power and stability were obtained in all cases. The observed binding modes are consistent with available experimental data on residues considered crucial for interactions with arylpiperazine compounds. The main results have indicated some important features for optimal binding to the 5-HT1A receptor, such as the presence of a benzothiophene ring as Ar2 substituent, small groups at position Z and hydrogen bond acceptors at the ortho position of Ar1 ring. These results were corroborated by modeling the interactions with the 5- HT1A receptor, which has indicated an important hydrophobic interaction between the benzothiophene group and residue Trp6.48, a hydrogen bond between the OH group at position Z and residue Thr3.37, as well as between the oxygen in Ar1 and residue Asn7.39. The information gathered in these studies can be useful for the design of new ligands displaying affinity to the 5-HT1A receptor.

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Carvalho, Luciana Luzia de. "Modelagem molecular de uma série de compostos inibidores da enzima integrase do vírus HIV-1." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/75/75131/tde-16092011-160536/.

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Uma etapa essencial no ciclo de vida do vírus HIV é a integração do DNA viral no cromossomo hospedeiro. Essa etapa é catalisada pela enzima integrase (IN) de 32-kDa. HIV-1 IN é um importante e validado alvo, e as drogas que inibem seletivamente a enzima, quando utilizadas em combinação com os inibidores da transcriptase reversa (RT) e protease (PR), são consideradas altamente eficazes em suprimir a replicação viral. IN catalisa dois processos enzimáticos designados por 3\' processamento e transferência de DNA. Agentes ativos contra integrase, inibindo a etapa de transferência da vertente já estão em fase clínica. O fármaco Raltegravir® é o primeiro nesta nova classe. Os ensaios clínicos no tratamento em novos pacientes têm uma atividade anti-retroviral potente e bem tolerado. Dada a sua potência, segurança e novo mecanismo de ação, os inibidores da integrase representam um importante avanço terapêutico contra o HIV-1. Na presente tese de doutorado, foram realizados estudos quimiométricos utilizando descritores teóricos e QSAR bi- (2D) e tridimensionais (3D) empregando, respectivamente, as técnicas holograma QSAR (HQSAR) e a análise comparativa dos campos moleculares (CoMFA), visando à geração de modelos preditivos para um conjunto de inibidores da integrase do vírus HIV-1. Modelos de QSAR com boa consistência interna, habilidade preditiva e estabilidade foram obtidos em todos os casos. Os modelos gerados, associados às informações obtidas pelos mapas de contribuição 2D e de contorno 3D, são guias químico-medicinais úteis no planejamento de novos inibidores mais potentes e seletivos da integrase do HIV-1.
An essential step in the HIV life cycle is integration of the viral DNA into the host chromosome. This step is catalyzed by a 32-kDa viral enzyme HIV integrase (IN). HIV-1 IN is an important and validated target, and the drugs that selectively inhibit this enzyme, when used in combination with reverse transcriptase (RT) and protease (PR) inhibitors, are believed to be highly effective in suppressing the viral replication. IN catalyzes two discrete enzymatic processes referred as 3\' processing and DNA strand transfer. Agents active against HIV-1, which target the viral integrase by inhibiting the strand transfer step of integration, have now initialized the clinical trials. The Raltegravir® is the first drug in this new class. Clinical trials in treatment-experienced and in treatment-naive patients have shown that raltegravir-containing regimens have potent antiretroviral activity and are well tolerated. Given their potency, safety and novel mechanism of action, integrase inhibitors represent an important advance in HIV-1 therapy. In the present thesis, Bi- and Tridimensional Quantitative Structure-Activity Relationship (QSAR) studies were performed applying chemometric methods based on theoretical descriptors, Comparative Molecular Field Analysis (CoMFA) and Holograma QSAR (HQSAR) techniques, aiming to generate predictive models for a large set of HIV-1 IN inhibitors. QSAR models presenting good internal consistency, predictive power and stability were obtained in all cases. The final models along with the information resulted by 2D contribution and 3D contour maps should be useful in the design of new inhibitors with increased potency and selective within the chemical diversity of the data.

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Costa, Raimundo Nonato Pereira da. "Estudo da atividade antineoplásica das carboquinonas através de descritores quânticos." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/277633.

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Orientador: Douglas Soares Galvão
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Fisica Gleb Wataghin
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Resumo: A descoberta de tratamentos eficazes contra o câncer é um dos maiores desafios da ciência. No Brasil o câncer se tornou a segunda maior causa de morte. As estimativas para o ano de 2005 apontam que ocorrerão 467.440 casos novos de câncer. O investimento para o desenvolvimento de uma droga moderna é de U$850milhões e o tratamento com estas variam de U$4000 a U$17000 por mês. Estudos de relação atividade-estrutura (SAR) quantitativa têm um importante papel no design de drogas. Neste trabalho foi aplicado a Metodologia de Índices Eletrônicos (MIE) para estudar a correlação da atividade antineoplásica de 36 moléculas derivadas das carboquinonas. A MIE é baseada nos conceitos de densidade local de estado, da qual se extrai o índice D, e na diferença de energia dos estados de fronteira, índice h , obtidos por cálculo de mecânica quântica ab initio ou semi-empírico. Os cálculos foram efetuados utilizando o método PM3 (Parametric Method 3) disponível no pacote computacional MOPAC. Os resultados demonstram que a MIE consegue diferenciar com uma precisão de 92% os compostos mais ativos biologicamente. A Análise de Principal Componente (PCA), utilizando-se os parâmetros da MIE, resultou em 100% de acerto na diferenciação da atividade biológica, enquanto com o método de análise hierárquica de grupo (HCA) obteve-se padrão de agrupamento com 94% de acerto. Concluímos que o uso dos índices D e h pode ser uma eficaz ferramenta para estudos de relação atividade-estrutura qualitativa das carboquinonas e para o desenvolvimento e aprimoramento de novas drogas
Abstract: The discovery of efficient treatments against cancer is one of the great challenges of science. In Brazil the cancer became the second greatest cause of death. For the year 2005 467,440 new cases of cancer are expected. The investment for the development of a modern drug is about U$ 850 millions and the treatment with those drugs varies from U$ 4,000 to U$ 17,000 per month. Structure-Activity Relationship (SAR) studies play an important role in design of drugs. In this work the Methodology of Electronic Indices was applied (MEI) to the study of anticancer activity of 36 molecules derived from carboquinones. The MEI is based on the concepts of local density of states, from which the index D is extracted, and in the difference of energy of the frontier orbitals, which defines the other MEI parameter h. The geometrical and electronic aspects for the carboquinone set were obtained using the semi-empirical PM3 (Parametric Method 3) available in computational package MOPAC. Our results show that the MEI is able to classify (with an accuracy of 92%) active and inactive compounds. More standards statistical methods such Principal Component Analysis (PCA) and Hierarchic Cluster Analysis (HCA) were also used also producing results of identifying active/inactive molecules with high accuracy (100 and 94%, respectively). We conclude that the use of the MEI indices D and h can be an efficient tool for studies of qualitative SAR studies of carboquinones, as well as, to be used for the development and improvement of new drugs
Mestrado
Estrutura, Conformação e Estereoquimica
Mestre em Física

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Reddy, Badinehal Asrith. "COMMERCIALIZATION OF A QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP TOOL - SARCHITECT." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1295637833.

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Prouillac, Caroline. "Synthèse et évaluation de nouveaux composés organiques et phosphorés contre les effets des rayonnements ionisants : étude de leur mécanisme d’action in vitro." Toulouse 3, 2006. http://www.theses.fr/2006TOU30152.

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Ce travail s’inscrit dans un programme de recherche visant à synthétiser de nouveaux composés organiques et phosphorés possédant un rapport activité/toxicité convenable. Pour cela, nous avons réalisé la synthèse de nouveaux motifs N-substitués du benzothiazole et du thiadiazole tels que des thiols, aminothiols, acides thiosulfoniques et phosphorothioates. Tous ces composés ont été caractérisés physico-chimiquement par spectroscopie RMN (proton, carbone, phosphore, 2D), par spectrométrie de masse, analyse élémentaire et pour certains d’entre eux par diffraction des rayons X. L’activité de la plupart des composés a été évaluée par des tests in vitro. Les résultats expérimentaux ont été confirmés par des calculs théoriques de DFT visant à étudier le mécanisme de capture des radicaux libres par nos composés. D’autre part, une étude de relation structure activité (QSAR) a été réalisée. Les résultats nous ont permis d’élaborer un modèle permettant d’établir une relation structure-activité
This work falls under a research program. The aim was to synthesize new organic phosphorylated compounds having an interesting radiopharmacological activity without toxicity. That’s why, we carried out the synthesis of new benzothiazole and thiadiazole N-substituted derivatives as thiols, aminothiols, acids thiosulfonic and phosphorothioates. All these compounds were characterized by NMR (proton, carbon, phosphorus, 2D), by mass spectrometry, elementary analyzes and for some of them by diffraction of x-rays. The activity of the majority of them was evaluated by in vitro tests. The experimental results were confirmed by theoretical study : the aim of DFT calculation was the study of the mechanism of capture of the free radicals by our compounds. In addition, a study of relation structure activity (QSAR) was carried out. Our results allow us to create a model making it possible to establish structure-activity relationship

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Willmes, Thomas [Verfasser]. "Synthese, Testung und 3D-QSAR von ABCG2-Inhibitoren / Thomas Willmes." Bonn : Universitäts- und Landesbibliothek Bonn, 2021. http://d-nb.info/1240761309/34.

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Келеберда, Антон Миколайович. "Програмна система QSAR моделювання для оцінки здатності блокування реплікації ВІЛ." Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/34639.

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Робота присвячена розробці програми для прогнозування здатності різних хімічних сполук блокувати реплікацію вірусу імунодефіциту людини, а також для оцінки побічних дій препаратів. У зв’язку з актуальністю проблеми поширення ВІЛ/СНІДу виникає потреба у пошуку профілактичних заходів для запобігання цієї проблеми. Запропонований метод полягає у пошуку хімічних сполук, здатних повністю або частково блокувати реплікацію вірусу імунодефіциту людини в організмі.
The work is devoted to the development of a program for predicting the ability of various chemical compounds to block the replication of human immunodeficiency virus, and also for assessing the side effects of drugs. Due to the urgency of the problem of the spread of HIV/AIDS, there is a need to seek preventive measures to prevent this problem. The proposed method is to search for chemical compounds that can completely or partially block the replication of human immunodeficiency virus in the body.

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Rodgers, Amie D. Rusyn Ivan. "Modeling adverse liver effects of drugs using kNN QSAR method." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2009. http://dc.lib.unc.edu/u?/etd,2463.

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Thesis (M.S.)--University of North Carolina at Chapel Hill, 2009.
Title from electronic title page (viewed Sep. 3, 2009). "... in partial fulfillment of the requirements for the degree of Masters of Sciences in the School of Medicine Toxicology." Discipline: Toxicology; Department/School: Medicine.

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Spreafico, Morena. "Mixed-model QSAR at the glucocorticoid and liver X receptors /." [S.l.] : [s.n.], 2009. http://edoc.unibas.ch/diss/DissB_8730.

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Silva, Aldineia Pereira da. "Estudo da relação estrutura-atividade de compostos biologicamente ativos derivados do aripiprazol." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/75/75134/tde-03072014-163248/.

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A esquizofrenia é uma doença que, de acordo com a Organização Mundial de Saúde, acomete cerca de 1% da população mundial. Tendo em vista a sua alta incidência e, portanto, sua relevância, o presente trabalho objetivou estudar uma classe de compostos derivados do aripiprazol, substância ativa que estimula os receptores dopaminérgicos e serotoninérgicos, receptores esses de suma importância para o entendimento da fisiopatologia da esquizofrenia. Para isso, o estudo de QSAR foi realizado através dos métodos PLS e ANN, gerando dois modelos para tentar entender a relação entre a estrutura química e a atividade biológica. Os dois modelos gerados, PLS e ANN, foram satisfatórios, explicando 82,52% e 72,90% respectivamente, da variabilidade da atividade biológica. No entanto, como o modelo obtido através do método PLS foi considerado melhor, conclui-se que as variáveis selecionadas possuem comportamento linear frente à atividade biológica.
The Schizophrenia is a disease that affects about 1% of world population, according to the World Health Organization. Looking into its high incidence and therefore its relevance, the goal of this study was to investigate a class of compounds derived from aripiprazole, the active substance that stimulates dopamine and serotonin receptors, those essential for understanding the pathophysiology of schizophrenia. For the investigation to go on, the QSAR study was performed through PLS and ANN methods, generating two models in order to understand the relationship between chemical structure and biological activity. Both model results, PLS and ANN, were considered satisfactory, explaining 82.52% and 72.90%, respectively, of the variability of the biological activity. However, since the model obtained by the PLS method showed more satisfactory results, it can be concluded that the selected variables have a linear behavior concerning the biological activity.

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35

Nagurniak, Gláucio Regis. "Análise da relação entre a estrutura química e a atividade biológica de antagonistas moleculares do receptor μ-opióide." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/75/75134/tde-30072013-093119/.

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Desde os tempos antigos, o leite de papoula é usado como sedativo e poderoso analgésico. Hoje, na terapêutica, a morfina - a qual se encontra em grande proporção no leite da papoula - continua sendo utilizada como analgésico em casos de dor moderada e severa. Concomitantemente, drogas derivadas da morfina têm sido amplamente utilizadas; sendo a heroína uma das drogas com maior potencial viciante conhecido.
O desenvolvimento de antagonistas do receptor alvo da morfina/heroína (receptor μ-opioide) pode auxiliar tanto no desenvolvimento de medicamentos analgésicos mais seguros e potentes, bem como no desenvolvimento de medicamentos que podem ter utilidade no tratamento da dependência por drogas opiáceas.
Com o intuito de criar a relação entre a atividade biológica de um conjunto de 51 moléculas e sua respectiva ação antagonista ao receptor μ-opioide, foram selecionadas, da literatura, moléculas que apresentam interações biológicas contra o receptor μ-opioide.
As moléculas selecionadas tiveram suas geometrias otimizadas e suas propriedades calculadas pelo método DFT/B3LYP, com um conjunto de funções de base 6-31g++(d,p). Os dados obtidos, como informações sobre a estrutura eletrônica, propriedades topológicas e físico-químicas, foram relacionados com os valores de pKi. Para a correta análise das variáveis que são úteis na descrição da atividade biológica, métodos de análise estatística como PCA, HCA, SIMCA e KNN foram utilizados, além do método de PLS para a construção do modelo matemático de relação entre atividade biológica e as variáveis.
Os resultados mostram que variáveis como a energia do orbital LUMO, a quantidade de nitrogênios na cadeia da molécula, o volume de alguns substituintes e o valor das variáveis E1p e E3u (mensuradas respectivamente pela polarizabilidade molecular e peso atômico) têm grande relação com a atividade biológica.
O modelo criado é útil na previsão da atividade biológica de outras moléculas, bem como ao fornecer ideias para uma síntese planejada de novos compostos com atividade antagonista promissora.
Since antiquity, the poppy\'s milk has been used as sedative and powerful analgesic. Nowadays, in the therapy, the morphine - that is found in large proportion in poppy\'s milk - is still being used as painkiller in cases of moderate and severe pain. Concurrently, drugs made from morphine have been widely used; being the heroin the drug with the highest known addictive potential.
The development of the antagonists of the morphine/heroine target receptor (μ-opiate receptor) can help on more safety and powerful medicine developments, and also to develop medicines that can be useful in treating opiate drugs addiction.
In order to create the relationship between biological activity of a set of 51 molecules and their respective antagonist action by μ-opiate receptor, was selected, from the literature, molecules that show biological interaction against μ-opiate receptor.
The selected molecules had their geometries optimized and their properties calculated by DFT/B3LYP method, with a set of base functions 6-31g++(d,p). The data obtained, as information about the electronic structure, topological properties and physical-chemical, were related to the pKi values. To the correct analysis of the variables that are useful on the description of the biological activity, were used statistical analysis methods as PCA, HCA, SIMCA and KNN, other than the PLS method for building the mathematical model of relationship between the biological activity and the variables.
The results show that variables as the energies of LUMO orbital, the quantity of nitrogen in the molecular chain, the volume of some substituents and the value of the variables E1p and E3u (measured respectively by molecular polarity and atomic weight) has big relationship with the biological activity.
The created model is useful in biological activity prevision for other molecules, as well as providing ideas for a planned synthesis of new compounds with promissory antagonist activity.

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36

Brunberg, Ingo. "Computeranwendungen in der Chemie Visualisierung chemischer Reaktionen und Generierung von QSAR-Modellen /." [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=964795787.

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37

Masunari, Andrea. "Planejamento, desenvolvimento e estudos de QSAR-2D e QSAR-3D de derivados 5-nitro-2-tiofilidênicos com atividade frente a Staphylococcus aureus multi-resistente (CEB - Clone Endêmico Brasileiro)." Universidade de São Paulo, 2005. http://www.teses.usp.br/teses/disponiveis/9/9135/tde-04102007-114357/.

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A reemergência de algumas bactérias Gram-positivas, em particular, do gênero Staphylococcus, como principal foco causador de infecções hospitalares, tem se intensificado nas últimas décadas, e, apesar da existência de potentes fármacos voltados para o tratamento de infecções causadas por este gênero de bactéria, as taxas de morbidade e mortalidade prevalecem com perfil crescente. Além disso, um grande problema associado a cepas de MRSA (Methicillin-Resistant Staphylococcus aureus) é o fenótipo de multi-resistência, característica que confere a este microrganismo resistência não apenas à meticilina como também a uma série de outros fármacos, exceto frente à vancomicina e à teicoplanina. Muito tem se feito, mas ainda são poucos os resultados efetivamente aplicáveis no tratamento de infecções com caráter de multi-resistência, justificando, desta forma, a necessidade de desenvolvimento de sucedâneos que sejam consideravelmente mais efetivos para a solução deste problema. Baseado nestes fatos, a proposta deste estudo envolveu o planejamento, síntese, identificação e estudos de QSAR (Quantitative Structure-Activity Relationships) em duas e três dimensões de derivados 5-nitro-2-tiofilidênicos com atividade antimicrobiana frente a cepas padrão e multi-resistente de Staphylococcus aureus. A escolha dos grupos substituintes foi realizada em duas etapas. Na primeira delas seguiu-se metodologia de substituição em anéis aromáticos proposta por Topliss para a otimização da bioatividade de compostos. Em uma segunda etapa, predominantemente quantitativa, foram selecionados mais alguns derivados baseando-se em faixa de hidrofobicidade ótima pré-determinada experimentalmente e na variação de efeito estérico dos grupos substituintes. Quatorze derivados 5-nitro-2-tiofilidênicos foram sintetizados, estruturalmente identificados e avaliados quanto à atividade antimicrobiana frente às cepas padrão (ATCC 25923) e multi-resistente (3SP/R33) de Staphylococcus aureus por determinação da concentração inibitória mínima empregando-se método de macrodiluição sucessiva em tubos. Salienta-se que a cepa 3SP/R33 se mostra resistente a dezenove antibióticos empregados na prática médica e apresenta suscetibilidade apenas à vancomicina. As concentrações inibitória e bactericida mínimas apresentadas pelos compostos sintetizados mostraram sofrer influência significativa da hidrofobicidade sobre as referidas atividades de acordo com os estudos de QSAR-2D e QSAR-3D, sendo os resultados obtidos para a cepa multi-resistente absolutamente compatíveis com os anteriormente determinados para a cepa padrão. Os estudos de QSAR-2D indicaram que a atividade antimicrobiana das 5nitro-2-tiofilideno benzidrazidas substituídas sofre influência significativa de duas propriedades físico-químicas que são a hidrofobicidade e a distribuição eletrônica. A relevância dos descritores estruturais σ e efe na determinação da atividade antimicrobiana, sinalizam que a distribuição eletrônica influencia fortemente o aumento da potência antimicrobiana dos compostos em estudo tanto pela influência dos efeitos indutivo e de ressonância na estrutura química do ligante, como também pelos campos moleculares gerados ao redor de grupos substituintes, sugerindo uma possível interação dos mesmos com uma área específica do sítio receptor. Nos estudos de QSAR-3D, foi evidenciado, em concordância com o estudo clássico anteriormente realizado, que a hidrofobicidade prevalece como propriedade de fundamental importância no estabelecimento da atividade antimicrobiana. Foi observada a importância da presença de regiões hidrofílicas pontuais nos compostos de forma a propiciar processos de solvatação e dessolvatação que são críticos na difusão através de membranas biológicas. Pode-se afirmar que a análise de QSAR, considerando os aspectos tridimensionais ligantes, ressaltou a necessidade de um balanço lipofílico-hidrofílico para um bom desempenho das 5-nitro-2-tiofilideno benzidrazidas ρ-substituídas como agentes antimicrobianos. A partir dos resultados obtidos evidenciou-se, neste estudo, o forte potencial de derivados 5-nitro-2-tiofilidênicos como possível alternativa para o desenvolvimento racional, em nível molecular, de fármacos voltados para o tratamento de infecções causadas por cepas multi-resistentes de Staphylococcus aureus.
In the last decade, there has been a reemergence of Gram-positive bacteria, in particular Staphylococcus, which isconsidered one of the. most causing of nosocomial infections. Although potent antistaphylococcal drugs are available, this infection continues presenting increasing morbidity and mortality rates. Besides, a serious problem associated with MRSA (Methicillin-Resistant Staphylococcus aureus) is the phenotype of multidrug resistance, which is, resistance not only to methicillin but also to many other drugs, except to vancomycin and teicoplanin. Many efforts have been made in a tentative to reduce this problem, nevertheless there is only a few number of alternatives to combat Staphylococcus aureus multidrug-resistant strains, justifying the necessity of development of more effective compounds to the treatment of these infections. Based in these facts, the purpose of this study was the design, synthesis, structural identification and 2D-QSAR and 3D-QSAR (Quantitative Structure-Activity Relationships) studies of 5-nitro-2-thiophylidene derivatives with antimicrobial activity against multidrug-resistant strains of Staphylococcus aureus. The choice of substituent groups was made in two stages. The first stage comprises on application of Topliss operational scheme for aromatic substitution. In a second quantitative stage, more derivatives were selected according by hydrophobicity range previously determined. Other standard considered at the selection of substituent groups was the variation of steric effect. Fourteen 5-nitro-2-thiophylidene derivatives were synthesized, structural identified and tested against standard (A TCC 25923) and multidrug-resistant (3SP/R33) strains of Staphylococcus aureus. The Minimal Inhibitory Concentration, MIC, was determined using the serial dilution tests in two sequential stages. The 3SP/R33 strain is resistant to nineteen antimicrobial agents in use, except to vancomycin. The minimal inhibitory and bactericidal concentrations of synthesized compounds showed, according by 2D-QSAR and 3D-QSAR studies, a significant influence of hydrophobic properties on antimicrobial activity determination and the results obtained for multidrug-resistant strain were consistent with those determined for A TCC 25923 strain. 2D-QSAR studies showed that antimicrobial activity are mainly influenced by two physico-chemical properties: hydrophobicity and electronic distribution. The relevance of σ e ephe parameters on antimicrobial activity determination, denotes the contribution of inductive and resonance effects for the polar performed by the substituent groups, probably suggesting an interaction between them and specific receptor site. 3D-QSAR studies showed that hydrophobicity is a essential property to antimicrobial activity determination, sustained the same conclusions previously obtained by Hansch Analysis. It was observed a great concern of small hydrophilic regions distributed on derivatives in order to promote solvation and desolvation process, that have critical importance on diffusion process through the biological membranes. QSAR studies considering three-dimensional properties of ligands indicated the necessity of accurate hydrophilic-hydrophobic balance on nitrothiophene derivatives for their good performance as antimicrobial agents. The results obtained in this preliminary study have shown the potential of synthesized compounds as alternatives to the treatment of infections caused by multidrug-resistant strains of Staphylococcus aureus.

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38

Canault, Baptiste. "Développement d'une plateforme de prédiction in silico des propriétés ADME-Tox." Thesis, Orléans, 2018. http://www.theses.fr/2018ORLE2048/document.

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Dans le cadre de la recherche pharmaceutique, les propriétés relatives à l’Absorption, la Distribution, le Métabolisme, l’Elimination (ADME) et la Toxicité (Tox) sont cruciales pour le succès des phases cliniques lors de la conception de nouveaux médicaments. Durant ce processus, la chémoinformatique est régulièrement utilisée afin de prédire le profil ADME-Tox des molécules bioactives et d’améliorer leurs propriétés pharmacocinétiques. Ces modèles de prédiction, basés sur la quantification des relations structure-activité (QSAR), ne sont pas toujours efficaces à cause du faible nombre de données ADME-Tox disponibles et de leur hétérogénéité induite par des différences dans les protocoles expérimentaux, ou encore de certaines erreurs expérimentales. Au cours de cette thèse, nous avons d’abord constitué une base de données contenant 150 000 mesures pour une cinquantaine de propriétés ADME-Tox. Afin de valoriser l’ensemble de ces données, nous avons dans un deuxième temps proposé une plateforme automatique de création de modèles de prédiction QSAR. Cette plateforme, nommée MetaPredict, a été conçue afin d’optimiser chacune des étapes de création d’un modèle statistique, dans le but d’améliorer leur qualité et leur robustesse. Nous avons dans un troisième temps valorisé les modèles obtenus grâce à la plateforme MetaPredict en proposant une application en ligne. Cette application a été développée pour faciliter l’utilisation des modèles, apporter une interprétation simplifiée des résultats et moduler les observations obtenues en fonction des spécificités d’un projet de recherche. Finalement, MetaPredict permet de rendre les modèles ADME-Tox accessibles à l’ensemble des chercheurs
Absorption, Distribution, Metabolism, Elimination (ADME) and Toxicity (Tox) properties are crucial for the success of clinical trials of a drug candidate. During this process, chemoinformatics is regularly used to predict the ADME-Tox profile of bioactive compounds and to improve their pharmacokinetic properties. In silico approaches have already been developed to improve poor pharmacokinetics and toxicity of lead compounds. These predictive models, based on the quantification of structure-activity relationships (QSAR), were not always efficient enough due to the low number of accessible biological data and their heterogeneity induced by the differences in experimental assays or the significant experimental error. In this thesis, we first built a database containing 150,000 data points for about 50 ADME-Tox properties. In order to valorize all this data, we then proposed an automatic platform for creating predictive models. This platform, called MetaPredict, has been designed to optimize each step of model development, in order to improve their quality and robustness. Third,, we promoted the statistical models using the online application of MetaPredict platform. This application has been developed to facilitate the use of newly built models, to provide a simplified interpretation of the results and to modulate the obtained observations according to the needs of the researchers. Finally, this platform provides an easy access to the ADME-Tox models for the scientific community

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39

Gallegos, Saliner Ana. "Molecular quantum similarity in QSAR: applications in computer-aided molecular design." Doctoral thesis, Universitat de Girona, 2004. http://hdl.handle.net/10803/7937.

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La present tesi està centrada en l'ús de la Teoria de Semblança Quàntica per a calcular descriptors moleculars. Aquests descriptors s'utilitzen com a paràmetres estructurals per a derivar correlacions entre l'estructura i la funció o activitat experimental per a un conjunt de compostos. Els estudis de Relacions Quantitatives Estructura-Activitat són d'especial interès per al disseny racional de molècules assistit per ordinador i, en particular, per al disseny de fàrmacs.
Aquesta memòria consta de quatre parts diferenciades. En els dos primers blocs es revisen els fonaments de la teoria de semblança quàntica, així com l'aproximació topològica basada en la teoria de grafs. Ambdues teories es fan servir per a calcular els descriptors moleculars. En el segon bloc, s'ha de remarcar la programació i implementació de programari per a calcular els anomenats índexs topològics de semblança quàntica. La tercera secció detalla les bases de les Relacions Quantitatives Estructura-Activitat i, finalment, el darrer apartat recull els resultats d'aplicació obtinguts per a diferents sistemes biològics.
The present thesis is centred in the use of the Quantum Similarity Theory to calculate molecular descriptors. These molecular descriptors are used as structural parameters to derive correlations between the structure and the function or experimental activity for a set of compounds. Quantitative Structure-Activity Relationship studies are of special interest for the rational Computer-Aided Molecular Design and, in particular, for Computer-Aided Drug Design.
The memory has been structured in four differenced parts. The two first blocks revise the foundations of quantum similarity theory, as well as the topological approximation, based in classical graph theory. These theories are used to calculate the molecular descriptors. In the second block, the programming and implementation of Topological Quantum Similarity Indices must be remarked. The third section details the basis for Quantitative Structure-Activity Relationships and, finally, the last section gathers the application results obtained for different biological systems.

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40

Saunders, Robert Alun. "Molecular surface area measures of polarity and hydrogen bonding for QSAR." Thesis, Cardiff University, 2004. http://orca.cf.ac.uk/55146/.

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Modifications were made to the traditional PSA descriptor by decoupling it into its H-bond acidic and basic components. The PSA based descriptors were also scaled according to the known hydrogen bonding characteristics of common functional groups to make them more realistic measures of a molecules hydrogen bonding capacity. Three other surface area descriptors total surface area, total halogen atom surface area and total aromatic carbon surface area were also defined. Various routes to the calculation of these descriptors were explored and it was concluded the best descriptors were those obtained from a single structure generated using the semi empirical-method AMI. It was also shown that descriptors obtained from a vdw surface were more suitable than those obtained from solvent accessible surface area. The scaled PSA descriptors were initially tested against octanol-water, chloroform-water, and cyclohexane-water partition coefficients of 110 organic and drug-like molecules. All of the models produced were seen to be statistically accurate and followed known characteristics of the partition coefficients considered. The scaled PSA descriptors were then applied successfully to a number of important biological processes such as cellular uptake and intestinal absorption models were also produced for important industrial processes such as Fluorophilicity and CMC. The surface area descriptors were also seen to be equally capable of modelling inorganic molecules and excellent models were produced for octanol-water and chloroform-water partitions for a number of platinum containing drugs.

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Bueno, Renata Vieira. "Planejamento de novos candidatos a fármacos tuberculostáticos: modelagem molecular e QSAR." Universidade Federal de Goiás, 2013. http://repositorio.bc.ufg.br/tede/handle/tede/3324.

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Tuberculosis (TB) is a chronic infectious and contagious disease with high epidemiological rates. The rise of multi- and extensively drug-resistant strains as well as the side effects and the long term treatment become urgent the development of novel therapy options. The enzyme thymidine monophosphate kinase of Mycobacterium tuberculosis (TMPKmt) is essential to DNA synthesis and cell replication. Moreover, this enzyme has unique structural characteristics among TMPKs family, emerging as a potential target to rational design of novel anti-TB agents. The present work had as objective the application of Computer Aided Drug-Design (CADD) strategies, using a set of 109 thymidine analogues inhibitors of TMPKmt selected from the literature, aiming to elucidate the structural features relevant to the biological activity of this set of compounds and generate models able to predict the activity of untested compounds. Methodologies of 2D-QSAR (HQSAR), 3-D-QSAR (CoMFA and CoMSIA), QM/MM docking and bioisosteric fragment replacement were performed for proposing new TMPKmt inhibitors. The final models of HQSAR, CoMFA and CoMSIA exhibit good internal and external consistency, presenting good correlation ability and prediction of biological activity. The HQSAR contribution maps and the contour maps of CoMFA and CoMSIA provided important information about structural features related to affinity, such as the favorable presence of hydrophobic and less bulky substituents on thymine ring and more bulky, electronegative, hydrophilic and hydrogen acceptors on sulfone of naphtosultam ring. Gathering the information provided, it was planned nine new compounds as potential TMPKmt inhibitors, which showed optimized affinity and physicochemical properties.
A tuberculose (TB) é uma doença infecto-contagiosa crônica com altas taxas epidemiológicas. O surgimento de cepas multi- e extensivamente resistentes aos fármacos utilizados bem como os efeitos adversos e a longa duração do tratamento tornam urgente o desenvolvimento de novas opções terapêuticas. A enzima timidina monofosfato quinase de Mycobacterium tuberculosis (TMPKmt) é essencial para a síntese de DNA e replicação celular. Além disso, esta enzima possui características estruturais únicas na família de TMPKs, sendo um alvo potencial para o planejamento racional de novos agentes anti-TB. O presente trabalho objetivou a aplicação de estratégias de planejamento de fármacos auxiliado por computador (CADD), utilizando um conjunto de 109 análogos de timidina inibidores de TMPKmt selecionados da literatura, buscando-se elucidar os requisitos estruturais relevantes à atividade biológica dessa classe de compostos e gerar modelos capazes de prever a atividade de compostos ainda não testados. Utilizou-se metodologias de QSAR-2D (HQSAR), QSAR-3D (CoMFA e CoMSIA), docking QM/MM e substituição bioisostérica de fragmentos para a proposição de novos inibidores da TMPKmt. Os modelos finais de HQSAR, CoMFA e CoMSIA possuem elevada consistência interna e externa, apresentando bom poder de correlação e predição da atividade biológica. Os mapas de contribuição de HQSAR e os mapas de contorno de CoMFA e CoMSIA forneceram informações importantes sobre características estruturais relacionadas à afinidade, tais como a presença de substituintes hidrofóbicos e pouco volumosos no anel timina favorecerem a atividade, assim como a presença de grupos volumosos e com alta densidade eletrônica, hidrofílicos e aceptores de ligação de hidrogênio no grupo sulfona do anel naftosutâmico. Utilizando-se as informações obtidas, planejou-se nove novos compostos como possíveis inibidores de TMPKmt, que apresentaram afinidade e propriedades físico-químicas otimizadas. Estudos de docking evidenciaram que os dois hits mais potentes apresentam interações no sítio ativo da TMPKmt capazes de desestabilizar o processo catalítico entre a enzima e o substrato natural, indicando que os compostos propostos são potenciais inibidores da TMPKmt.

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42

Simões, Rodolfo da Silva. "Técnicas de transferência de aprendizagem aplicadas a modelos QSAR para regressão." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/100/100131/tde-07062018-120939/.

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Para desenvolver um novo medicamento, pesquisadores devem analisar os alvos biológicos de uma dada doença, descobrir e desenvolver candidatos a fármacos para este alvo biológico, realizando em paralelo, testes em laboratório para validar a eficiência e os efeitos colaterais da substância química. O estudo quantitativo da relação estrutura-atividade (QSAR) envolve a construção de modelos de regressão que relacionam um conjunto de descritores de um composto químico e a sua atividade biológica com relação a um ou mais alvos no organismo. Os conjuntos de dados manipulados pelos pesquisadores para análise QSAR são caracterizados geralmente por um número pequeno de instâncias e isso torna mais complexa a construção de modelos preditivos. Nesse contexto, a transferência de conhecimento utilizando informações de outros modelos QSAR\'s com mais dados disponíveis para o mesmo alvo biológico seria desejável, diminuindo o esforço e o custo do processo para gerar novos modelos de descritores de compostos químicos. Este trabalho apresenta uma abordagem de transferência de aprendizagem indutiva (por parâmetros), tal proposta baseia-se em uma variação do método de Regressão por Vetores Suporte adaptado para transferência de aprendizagem, a qual é alcançada ao aproximar os modelos gerados separadamente para cada tarefa em questão. Considera-se também um método de transferência de aprendizagem por instâncias, denominado de TrAdaBoost. Resultados experimentais mostram que as abordagens de transferência de aprendizagem apresentam bom desempenho quando aplicadas a conjuntos de dados de benchmark e a conjuntos de dados químicos
To develop a new medicament, researches must analyze the biological targets of a given disease, discover and develop drug candidates for this biological target, performing in parallel, biological tests in laboratory to validate the effectiveness and side effects of the chemical substance. The quantitative study of structure-activity relationship (QSAR) involves building regression models that relate a set of descriptors of a chemical compound and its biological activity with respect to one or more targets in the organism. Datasets manipulated by researchers to QSAR analysis are generally characterized by a small number of instances and this makes it more complex to build predictive models. In this context, the transfer of knowledge using information other\'s QSAR models with more data available to the same biological target would be desirable, nince its reduces the effort and cost to generate models of chemical descriptors. This work presents an inductive learning transfer approach (by parameters), such proposal is based on a variation of the Vector Regression method Adapted support for learning transfer, which is achieved by approaching the separately generated models for each task. It is also considered a method of learning transfer by instances, called TrAdaBoost. Experimental results show that learning transfer approaches perform well when applied to some datasets of benchmark and dataset chemical

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Briens, Frédérique. "Applicabilité de nouveaux descripteurs de QSAR en écotoxicologie : cas des chlorophénols." Caen, 1998. http://www.theses.fr/1998CAEN4001.

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Newby, Danielle Anne. "Data mining methods for the prediction of intestinal absorption using QSAR." Thesis, University of Kent, 2014. https://kar.kent.ac.uk/47600/.

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Oral administration is the most common route for administration of drugs. With the growing cost of drug discovery, the development of Quantitative Structure-Activity Relationships (QSAR) as computational methods to predict oral absorption is highly desirable for cost effective reasons. The aim of this research was to develop QSAR models that are highly accurate and interpretable for the prediction of oral absorption. In this investigation the problems addressed were datasets with unbalanced class distributions, feature selection and the effects of solubility and permeability towards oral absorption prediction. Firstly, oral absorption models were obtained by overcoming the problem of unbalanced class distributions in datasets using two techniques, under-sampling of compounds belonging to the majority class and the use of different misclassification costs for different types of misclassifications. Using these methods, models with higher accuracy were produced using regression and linear/non-linear classification techniques. Secondly, the use of several pre-processing feature selection methods in tandem with decision tree classification analysis – including misclassification costs – were found to produce models with better interpretability and higher predictive accuracy. These methods were successful to select the most important molecular descriptors and to overcome the problem of unbalanced classes. Thirdly, the roles of solubility and permeability in oral absorption were also investigated. This involved expansion of oral absorption datasets and collection of in vitro and aqueous solubility data. This work found that the inclusion of predicted and experimental solubility in permeability models can improve model accuracy. However, the impact of solubility on oral absorption prediction was not as influential as expected. Finally, predictive models of permeability and solubility were built to predict a provisional Biopharmaceutic Classification System (BCS) class using two multi-label classification techniques, binary relevance and classifier chain. The classifier chain method was shown to have higher predictive accuracy by using predicted solubility as a molecular descriptor for permeability models, and hence better final provisional BCS prediction. Overall, this research has resulted in predictive and interpretable models that could be useful in a drug discovery context.

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CONCU, RICCARDO. "New QSAR models based on Markov Chains to predict protein functions." Doctoral thesis, Università degli Studi di Cagliari, 2010. http://hdl.handle.net/11584/266281.

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Gaspar, Héléna Alexandra. "Cartography of chemical space." Thesis, Strasbourg, 2015. http://www.theses.fr/2015STRAF030/document.

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Cette thèse est consacrée à la cartographie de l’espace chimique ; son but est d’établir les bases d’un outil donnant une vision d’ensemble d’un jeu de données, comprenant prédiction d’activité, visualisation, et comparaison de grandes librairies. Dans cet ouvrage, nous introduisons des modèles prédictifs QSAR (relations quantitatives structure à activité) avec de nouvelles définitions de domaines d’applicabilité, basés sur la méthode GTM (generative topographic mapping), introduite par C. Bishop et al. Une partie de cette thèse concerne l’étude de grandes librairies de composés chimiques grâce à la méthode GTM incrémentale. Nous introduisons également une nouvelle méthode « Stargate GTM », ou S-GTM, permettant de passer de l’espace des descripteurs chimiques à celui des activités et vice versa, appliquée à la prédiction de profils d’activité ou aux QSAR inverses
This thesis is dedicated to the cartography of chemical space; our goal is to establish the foundations of a tool offering a complete overview of a chemical dataset, including visualization, activity prediction, and comparison of very large datasets. In this work, we introduce new QSAR models (quantitative structure-activity relationship) based on the GTM method (generative topographic mapping), introduced by C. Bishop et al. A part of this thesis is dedicated to the visualization and analysis of large chemical libraries using the incremental version of GTM. We also introduce a new method coined “Stargate GTM” or S-GTM, which allows us to travel from the space of chemical descriptors to activity space and vice versa; this approach was applied to activity profile prediction and inverse QSAR

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Lipinski, Célio Fernando. "Estudo de relações quantitativas estrutura-atividade de chalconas análogas à combretastatina A4." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/75/75134/tde-07052015-112219/.

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A combretastatina A4 é um promissor agente anticâncer. Na célula, inibe a polimerização dos microtúbulos, os quais são fundamentais nos processos de motilidade, manutenção estrutural e mitose. Essa inibição se dá a partir do sítio de interação da αβ-tubulina bloqueando o fluxo do sangue que alimenta os tumores, o que resulta na morte dos mesmos. Com estrutura semelhante às combretastatinas, as chalconas constituem uma classe de compostos que atuam no mesmo sítio de interação na tubulina. Baseando-se nos trabalhos experimentais de Ducki e colaboradores, estudou-se a estrutura molecular de 87 chalconas análogas à combretastatina A4 por meio do método quântico DFT com o propósito de desenvolver modelos de Relações Quantitativas Estrutura-Atividade (QSAR) aplicados a tais antagonistas. A partir dos métodos dos Mínimos Quadrados Parciais (PLS) e de Redes Neurais Artificiais (ANN), foram gerados modelos que conduzem à elucidação da relação dos compostos estudados com suas respectivas atividades biológicas. Os descritores eletrônicos e moleculares selecionados apresentam alta concordância com as características das moléculas, havendo predominância de comportamento linear com a atividade biológica, podendo, eventualmente, apresentar comportamento não-linear, o que torna o modelo gerado altamente consistente.
Combretastatin A4 is a promising anticancer agent. It inhibits the polymerization of microtubules in the cell, which are essential in the process of motility, structural maintenance and mitosis. This inhibition is given from the interaction site of αβ-tubulin blocking the blood flow that feeds the tumor, what results in its death. The chalcones, sharing a similar structure of the combretastatin, are also a class of compounds that act in the same site of interaction in the tubulin. Based on the experimental work of Ducki and co-workers, we proposed a molecular structure study of 87 chalcones similar to combretastatin A4 using the DFT method in order to develop Quantitative Structure-Activity Relationships (QSAR) applied to the given antagonists. Through Partial Least Squares (PLS) and Artificial Neural Network (ANN) methods, some models has been generated to lead the understanding on the relationship between the compounds studied and their respective biological activities. The electronic and molecular descriptors selected have high correlation with the molecule features, being linear most of the time, although with eventual non-linear behavior, which makes the generated model highly consistent.

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Miller, Matthew Dean Holder Andrew J. "Applications of quantum chemistry to polymerization reactions and biological activity." Diss., UMK access, 2004.

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Thesis (Ph. D.)--Dept. of Chemistry and School of Pharmacy. University of Missouri--Kansas City, 2004.
"A dissertation in chemistry and pharmaceutical science." Advisor: Andrew J. Holder. Typescript. Vita. Description based on contents viewed Feb. 27, 2006; title from "catalog record" of the print edition. Includes bibliographical references (leaves 206-221). Online version of the print edition.

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Tämm, Kaido. "QSPR modeling of some properties of organic compounds /." Online version, 2006. http://dspace.utlib.ee/dspace/bitstream/10062/475/5/tammkaido.pdf.

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Fouchault, Isabelle. "Intérêt des relations structures-activités dans l'évaluation des risques liés aux substances chimiques." Rouen, 1992. http://www.theses.fr/1992ROUE06NR.

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La Communauté Européenne Economique a répertorié 100116 substances chimiques dites "anciennes" pour lesquelles il n'y a pas ou peu d'informations toxicologiques et éco-toxicologiques. L'établissement de relations structures - activités (détermination de l'activité biologique à partir des propriétés structurales de la moléculaires) doit permettre de pallier à ce manque de données. Pour essayer d'établir ces relations structures-activités, un fichier de 667 substances répertoriant des paramètres chimiques et biologiques a été constitué. Le traitement des données par Analyse des données par Analyse en Composantes Principales a permis d'établir la redondance des variables suivantes : hydrosolubilité / coefficient de partage entre l'eau et l'octanol; pression de vapeur/ point de fusion/ point d'ébullition; doses léthales mammifères; doses léthales poissons; concentration léthales micro-custacés; concentration inhibitrices minimales algues. Les relations structures - activités obtenues à partir de ce fichier concernent : l'hydrosolubillité et la concentration léthale poissons établies par Analyses en Composantes Principales et par Régressions Multiples; les fonctions chimiques, le squelette carboné auquel elles sont rattachées et les doses léthales mammifères et concentrations léthales poisson établies par Analyse Factorielle des Correspondances.

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Dissertations / Theses on the topic 'QSAR'

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