Relevant bibliographies by topics / Pharmacophore models

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Pharmacophore models'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Pharmacophore models"

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Kutlushina, Alina, Aigul Khakimova, Timur Madzhidov, and Pavel Polishchuk. "Ligand-Based Pharmacophore Modeling Using Novel 3D Pharmacophore Signatures." Molecules 23, no. 12 (2018): 3094. http://dx.doi.org/10.3390/molecules23123094.

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Pharmacophore modeling is a widely used strategy for finding new hit molecules. Since not all protein targets have available 3D structures, ligand-based approaches are still useful. Currently, there are just a few free ligand-based pharmacophore modeling tools, and these have a lot of restrictions, e.g., using a template molecule for alignment. We developed a new approach to 3D pharmacophore representation and matching which does not require pharmacophore alignment. This representation can be used to quickly find identical pharmacophores in a given set. Based on this representation, a 3D pharm
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Madzhidov, Timur I., Assima Rakhimbekova, Alina Kutlushuna, and Pavel Polishchuk. "Probabilistic Approach for Virtual Screening Based on Multiple Pharmacophores." Molecules 25, no. 2 (2020): 385. http://dx.doi.org/10.3390/molecules25020385.

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Pharmacophore modeling is usually considered as a special type of virtual screening without probabilistic nature. Correspondence of at least one conformation of a molecule to pharmacophore is considered as evidence of its bioactivity. We show that pharmacophores can be treated as one-class machine learning models, and the probability the reflecting model’s confidence can be assigned to a pharmacophore on the basis of their precision of active compounds identification on a calibration set. Two schemes (Max and Mean) of probability calculation for consensus prediction based on individual pharmac
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Polishchuk, Pavel, Alina Kutlushina, Dayana Bashirova, Olena Mokshyna, and Timur Madzhidov. "Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations." International Journal of Molecular Sciences 20, no. 23 (2019): 5834. http://dx.doi.org/10.3390/ijms20235834.

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Pharmacophore models are widely used for the identification of promising primary hits in compound large libraries. Recent studies have demonstrated that pharmacophores retrieved from protein-ligand molecular dynamic trajectories outperform pharmacophores retrieved from a single crystal complex structure. However, the number of retrieved pharmacophores can be enormous, thus, making it computationally inefficient to use all of them for virtual screening. In this study, we proposed selection of distinct representative pharmacophores by the removal of pharmacophores with identical three-dimensiona
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Mortier, Jérémie, Pratik Dhakal, and Andrea Volkamer. "Truly Target-Focused Pharmacophore Modeling: A Novel Tool for Mapping Intermolecular Surfaces." Molecules 23, no. 8 (2018): 1959. http://dx.doi.org/10.3390/molecules23081959.

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Pharmacophore models are an accurate and minimal tridimensional abstraction of intermolecular interactions between chemical structures, usually derived from a group of molecules or from a ligand-target complex. Only a limited amount of solutions exists to model comprehensive pharmacophores using the information of a particular target structure without knowledge of any binding ligand. In this work, an automated and customable tool for truly target-focused (T²F) pharmacophore modeling is introduced. Key molecular interaction fields of a macromolecular structure are calculated using the AutoGRID
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Kumar, Saurav, Deepika Deepika, and Vikas Kumar. "Pharmacophore Modeling Using Machine Learning for Screening the Blood–Brain Barrier Permeation of Xenobiotics." International Journal of Environmental Research and Public Health 19, no. 20 (2022): 13471. http://dx.doi.org/10.3390/ijerph192013471.

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Daily exposure to xenobiotics affects human health, especially the nervous system, causing neurodegenerative diseases. The nervous system is protected by tight junctions present at the blood–brain barrier (BBB), but only molecules with desirable physicochemical properties can permeate it. This is why permeation is a decisive step in avoiding unwanted brain toxicity and also in developing neuronal drugs. In silico methods are being implemented as an initial step to reduce animal testing and the time complexity of the in vitro screening process. However, most in silico methods are ligand based,
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Gajjar, Krishna A., and Anuradha K. Gajjar. "Combiphore (Structure and Ligand Based Pharmacophore) - Approach for the Design of GPR40 Modulators in the Management of Diabetes." Current Drug Discovery Technologies 17, no. 2 (2020): 233–47. http://dx.doi.org/10.2174/1570163815666181008165822.

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Background: Pharmacophore mapping and molecular docking can be synergistically integrated to improve the drug design and discovery process. A rational strategy, combiphore approach, derived from the combined study of Structure and Ligand based pharmacophore has been described to identify novel GPR40 modulators. Methods: DISCOtech module from Discovery studio was used for the generation of the Structure and Ligand based pharmacophore models which gave hydrophobic aromatic, ring aromatic and negative ionizable as essential pharmacophoric features. The generated models were validated by screening
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Kadu, Nilesh S., and Atul V. Ingle. "Three-Dimensional Pharmacophore Modeling of Betulonic Acid Derivatives as a Strong Inhibitor of Human Coronavirus-229E Replication." International Journal of Science and Healthcare Research 6, no. 2 (2021): 356–61. http://dx.doi.org/10.52403/ijshr.20210462.

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These-days, pharmacophore approaches have become one of the foremost tools in drug discovery after the past century’s development. Numerous ligand-based and structure-based strategies are developed for improved pharmacophore modeling with success and extensively applied in virtual screening, de novo design and lead improvement. Till now, there is little information on 3D-pharmacophore studies of 1,2,3-triazolo-fused betulonic acid derivatives as a strong inhibitor for human coronavirus-229E replication. Here, we tend to report the appliance of pharmacophore modeling for betulonic acid derivati
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Wieder, Marcus, Ugo Perricone, Thomas Seidel, and Thierry Langer. "Pharmacophore Models Derived from Molecular Dynamics Simulations of Protein-Ligand Complexes: A Case Study." Natural Product Communications 11, no. 10 (2016): 1934578X1601101. http://dx.doi.org/10.1177/1934578x1601101019.

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A single, merged pharmacophore hypothesis is derived combining 2000 pharmacophore models obtained during a 20 ns molecular dynamics simulation of a protein-ligand complex with one pharmacophore model derived from the initial PDB structure. This merged pharmacophore model contains all features that are present during the simulation and statistical information about the dynamics of the pharmacophore features. Based on the dynamics of the pharmacophore features we derive two distinctive feature patterns resulting in two different pharmacophore models for the analyzed system – the first model cons
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Weng, Chia-Wei, Chi-Hsuan Wei, Jeng-Yuan Tsai, Yi-Hua Lai, Gee-Chen Chang, and Jeremy J. W. Chen. "Hybrid Pharmacophore- and Structure-Based Virtual Screening Pipeline to Identify Novel EGFR Inhibitors That Suppress Non-Small Cell Lung Cancer Cell Growth." International Journal of Molecular Sciences 23, no. 7 (2022): 3487. http://dx.doi.org/10.3390/ijms23073487.

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Dysregulated epidermal growth factor receptor (EGFR) expression is frequently observed in non-small cell lung cancer (NSCLC) growth and metastasis. Despite recent successes in the development of tyrosine kinase inhibitors (TKIs), inevitable resistance to TKIs has led to urgent calls for novel EGFR inhibitors. Herein, we report a rational workflow used to identify novel EGFR-TKIs by combining hybrid ligand- and structure-based pharmacophore models. Three types of models were developed in this workflow, including 3D QSAR-, common feature-, and structure-based EGFR-TK domain-containing pharmacoph
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Al-Sha'er, Mahmoud A., Rua'a A. Al-Aqtash та Mutasem O. Taha. "Discovery of New Phosphoinositide 3-kinase Delta (PI3Kδ) Inhibitors via Virtual Screening using Crystallography-derived Pharmacophore Modelling and QSAR Analysis". Medicinal Chemistry 15, № 6 (2019): 588–601. http://dx.doi.org/10.2174/1573406415666190222125333.

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<P>Background: PI3Kδ is predominantly expressed in hematopoietic cells and participates in the activation of leukocytes. PI3Kδ inhibition is a promising approach for treating inflammatory diseases and leukocyte malignancies. Accordingly, we decided to model PI3Kδ binding. </P><P> Methods: Seventeen PI3Kδ crystallographic complexes were used to extract 94 pharmacophore models. QSAR modelling was subsequently used to select the superior pharmacophore(s) that best explain bioactivity variation within a list of 79 diverse inhibitors (i.e., upon
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Dissertations / Theses on the topic "Pharmacophore models"

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Leite, Franco Henrique Andrade. "Planejamento e avalia??o de novos inibidores de Pteridina Redutase 1 (PTR1) de Leishmania major." Universidade Estadual de Feira de Santana, 2015. http://localhost:8080/tede/handle/tede/279.

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Submitted by Ricardo Cedraz Duque Moliterno (ricardo.moliterno@uefs.br) on 2016-01-13T23:50:52Z No. of bitstreams: 1 TESE-FINAL-FRANCO-HENRIQUE-CORRIGIDO-V4.pdf: 27152448 bytes, checksum: 7d448c937bb21040514eedeaa37f689f (MD5)<br>Made available in DSpace on 2016-01-13T23:50:52Z (GMT). No. of bitstreams: 1 TESE-FINAL-FRANCO-HENRIQUE-CORRIGIDO-V4.pdf: 27152448 bytes, checksum: 7d448c937bb21040514eedeaa37f689f (MD5) Previous issue date: 2015-11-06<br>Conselho Nacional de Pesquisa e Desenvolvimento Cient?fico e Tecnol?gico - CNPq<br>According to WHO, Leishmaniasis is the second most importa
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PERQUIS, FRANCOISE. "Analyse des proprietes pharmacologiques d'analogues structuraux de la minaprine par le biais d'un meme modele de pharmacophore." Strasbourg 1, 1994. http://www.theses.fr/1994STR15016.

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Aldhumani, Ali Hamed. "Pharmacophore Model Development: Targeting Noncoding RNA for Antibacterial/Antiviral Drug Discovery." Ohio University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1610705872573225.

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Hoffmann, Rémy Didier. "Ligands des recepteurs muscariniques m#1 : analyse conformationnelle et caracterisation d'un modele de pharmacophore." Université Louis Pasteur (Strasbourg) (1971-2008), 1993. http://www.theses.fr/1993STR13247.

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Le present memoire porte sur l'analyse structurale et conformationnelle de ligands muscariniques capables de se lier aux recepteurs muscariniques m#1 du cerveau. A partir d'une vingtaine d'agonistes et d'une vingtaine d'antagonistes capables de se lier a ces recepteurs, nous avons propose un modele de pharmacophore pour chacune de ces classes de molecules. Ces modeles, purement geometriques, permettent de reperer les positions relatives de differents groupements presents dans ces molecules: une tete cationique, une region electronegative pour les agonistes et les antagonistes, une region hydro
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DIDIER, BRUNO. "Analyse conformationnelle infographique et construction de pharmacophore : critique des methodes, description de systemes modeles et exemples d'application." Strasbourg 1, 1998. http://www.theses.fr/1998STR15065.

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Mitchell, Alesia S. "A semiempirical (am1) study of the reactivity of redox states of quin one-containing model systems for anthracycline pharmacophores." DigitalCommons@Robert W. Woodruff Library, Atlanta University Center, 1993. http://digitalcommons.auctr.edu/dissertations/3503.

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The reactivity of redox states of model systems for anthracycline pharmacophores were examined by the AM1 semiempirical approach. The redox states examined were quinone (Q), quinone radical anion (Q ), semiquinone radical (QH ), semiquinone anion (QH"), and hydroquinone (QH2), while the model systems were 1,4-benzoquinone (I), 1,4-naphthaquinone (II), hydroxy-naphthaquinone (III) and dihydroxy-naphthaquinone (IV), which are all part of the pharmacophores of several anthracyciines. The imine and/or diimine derivatives of 1,4-benzoquinone and dihydroxy-naphthaquinone were also investigated. The
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Haubner, Aaron Joseph. "DESIGN, SYNTHESIS, AND PHARMACOLOGICAL EVALUATION OF A SERIES OF NOVEL, GUANIDINE AND AMIDINE-CONTAINING NEONICOTINOID-LIKE ANALOGS OF NICOTINE: SUBTYPE-SELECTIVE INTERACTIONS AT NEURONAL NICOTINIC-ACETYLCHOLINE RECEPTOR." UKnowledge, 2008. http://uknowledge.uky.edu/gradschool_diss/621.

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The current project examined the ability of a novel series of guandine and amidine-containing nicotine analogs to interact with several native and recombinantlyexpressed mammalian neuronal nicotinic-acetylcholine receptor (nAChR) subtypes. Rational drug design methods and parallel organic synthesis was used to generate a library of guanidine-containing nicotine (NIC) analogs (AH compounds). A smaller series of amidine-containing nicotine analogs (JC compounds) were also synthesized. In total, >150 compounds were examined. Compounds were first assayed for affinity in a high-throughput [3H]epiba
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Paz, Odailson Santos. "Triagem in silico e avalia??o in vitro de compostos antifalcizantes." Universidade Estadual de Feira de Santana, 2017. http://localhost:8080/tede/handle/tede/496.

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Submitted by Ricardo Cedraz Duque Moliterno (ricardo.moliterno@uefs.br) on 2017-08-08T21:31:24Z No. of bitstreams: 1 TESE_Odailson Paz - com ficha.pdf: 4071411 bytes, checksum: 033f0c18eb721e7010e1ddd7ec27e10c (MD5)<br>Made available in DSpace on 2017-08-08T21:31:24Z (GMT). No. of bitstreams: 1 TESE_Odailson Paz - com ficha.pdf: 4071411 bytes, checksum: 033f0c18eb721e7010e1ddd7ec27e10c (MD5) Previous issue date: 2017-05-25<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES<br>Adenosine receptors are considered as potential targets for the development of drugs against dif
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Blake, Ava L. "Synthesis of Substituted Pyrimidines and Pyridines as Ligands to the 5-HT7 Receptor." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/chemistry_theses/29.

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Of the seven existing classes of serotonin receptors, the 5-HT7 receptors (5-HT7Rs) are the most recently discovered. Abundance of 5-HT7 in the central nervous system is suggestive of the receptor’s role in several physiological and pathophysiological functions. Existing research has afforded a number of compounds exhibiting specific affinity to the receptor. These selective ligands can provide structural information about the receptor and can serve as the foundation for pharmacological profiling . This thesis describes the synthesis of substituted pyrimidines and pyridines for affinity to the
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Réau, Manon. "Importance des données inactives dans les modèles : application aux méthodes de criblage virtuel en santé humaine et environnementale." Thesis, Paris, CNAM, 2019. http://www.theses.fr/2019CNAM1251/document.

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Le criblage virtuel est utilisé dans la recherche de médicaments et la construction de modèle de prédiction de toxicité. L’application d’un protocole de criblage est précédée par une étape d’évaluation sur une banque de données de référence. La composition des banques d’évaluation est un point critique ; celles-ci opposent généralement des molécules actives à des molécules supposées inactives, faute de publication des données d’inactivité. Les molécules inactives sont néanmoins porteuses d’information. Nous avons donc créé la banque NR-DBIND composée uniquement de molécules actives et inactive
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Book chapters on the topic "Pharmacophore models"

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Markt, Patrick, Daniela Schuster, and Thierry Langer. "Pharmacophore Models for Virtual Screening." In Methods and Principles in Medicinal Chemistry. Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527633326.ch5.

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Gillet, Valerie J. "Chapter 6. Pharmacophore Models in Drug Design." In Drug Discovery. Royal Society of Chemistry, 2012. http://dx.doi.org/10.1039/9781849735377-00151.

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Weber, Frauke, and Bernhard Wünsch. "Medicinal Chemistry of σ1 Receptor Ligands: Pharmacophore Models, Synthesis, Structure Affinity Relationships, and Pharmacological Applications." In Sigma Proteins: Evolution of the Concept of Sigma Receptors. Springer International Publishing, 2017. http://dx.doi.org/10.1007/164_2017_33.

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Bhattacharjee, Apurba K., Mark G. Hartell, Daniel A. Nichols, Rickey P. Hicks, John E. van Hamont, and Wilbur K. Milhous. "In Silico Three Dimensional Pharmacophore Models to Aid the Discovery and Design of New Antimalarial Agents." In Computational Science – ICCS 2006. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11758501_54.

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Takahashi, Mitsuo, Kuniya Sakurai, Seji Niwa, and Seiji Oono. "Pharmacophore Model of Endothelin Antagonists." In Molecular Modeling and Prediction of Bioactivity. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4141-7_103.

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Recanatini, Maurizio, Andrea Cavalli, and Matteo Masetti. "In Silico Modelling-Pharmacophores and hERG Channel Models." In The hERG Cardiac Potassium Channel: Structure, Function and Long QT Syndrome. John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/047002142x.ch14.

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Vrontaki, Eleni, and Antonios Kolocouris. "Pharmacophore Generation and 3D-QSAR Model Development Using PHASE." In Methods in Molecular Biology. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-8630-9_23.

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Boström, Jonas, Klaus Gundertofte, and Tommy Liljefors. "A 3D-Pharmacophore Model for Dopamine D4 Receptor Antagonists." In Molecular Modeling and Prediction of Bioactivity. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4141-7_87.

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Shim, Joong-Youn, Elizabeth R. Collantes, William J. Welsh, and Allyn C. Howlett. "Unified Pharmacophoric Model for Cannabinoids and Aminoalkylindoles." In Molecular Modeling and Prediction of Bioactivity. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4141-7_23.

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Rathi, E., A. Kumar, and S. G. Kini. "Identification of Potential VEGFR2 Inhibitors Employing E-pharmacophore Model, Virtual Screening, Molecular Dynamic Simulation and ADME Analysis." In Special Publications. Royal Society of Chemistry, 2019. http://dx.doi.org/10.1039/9781839160783-00040.

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Conference papers on the topic "Pharmacophore models"

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Djokovic, Nemanja, Ana Postolovic, and Katarina Nikolic. "MOLECULAR MODELING OF 5‐[(AMIDOBENZYL)OXY]‐ NICOTINAMIDES AS SIRTUIN 2 INHIBITORS USING ALIGNMENT- (IN)DEPENDENT 3D-QSAR ANALYSIS AND MOLECULAR DOCKING." In 1st INTERNATIONAL Conference on Chemo and BioInformatics. Institute for Information Technologies, University of Kragujevac, 2021. http://dx.doi.org/10.46793/iccbi21.410dj.

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The group of 5‐[(amidobenzyl)oxy]‐nicotinamides represents promising group of sirtuin 2 (SIRT2) inhibitors. Despite structural similarity, representatives of this group of inhibitors displayed versatile mechanisms of inhibition which hamper rational drug design. The aim of this research was to form a 3D-QSAR (3D-Quantitative Structure-Activity Relationship) model, define the pharmacophore of this subgroup of SIRT2 inhibitors, define the mode of protein-ligand interactions and design new compounds with improved predicted activity and pharmacokinetics. For the 3D-QSAR study, data set was generat
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Zhang, Xiao-Yi, Cun Xin Wang, and Kun Zeng. "Two Receptor Based Pharmacophore Models for HIV-1 Integrase DKA Inhibitors." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2009). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5163720.

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Zhang, Yanling, Yuanming Wang, and Yanjiang Qiao. "Structure-based pharmacophore models generation and Combinatorial Screening of ICE Inhibitors." In 2nd International Symposium on Computer, Communication, Control and Automation. Atlantis Press, 2013. http://dx.doi.org/10.2991/isccca.2013.110.

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Shih, Kuei-Chung, Chun-Yuan Lin, Jiayi Zhou, Shih-Han Huang, and Chuan-Yi Tang. "Develop integration modeling approach for discovery neuraminidase inhibitors in silico based on pharmacophore and CoMSIA models." In 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2010. http://dx.doi.org/10.1109/bibmw.2010.5703855.

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Raghavan, Sudhir, Aleem Gangjee, and Larry H. Matherly. "Abstract 1362: Novel proton coupled folate transporter (PCFT) and reduced folate carrier (RFC) pharmacophore models for development of transporter-selective antifolates." In Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1538-7445.am2016-1362.

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Yang, Zhen, Yanling Zhang, Xing Wang, and Yanjiang Qiao. "Pharmacophore Model Generation of P2Y12 Inhibitor." In 2012 International Conference on Biomedical Engineering and Biotechnology (iCBEB). IEEE, 2012. http://dx.doi.org/10.1109/icbeb.2012.293.

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Zhang, Dajin, Tong Xin, Xiangyan Xu, et al. "Virtual Screening of Iridoids SGLT2 Inhibitors Based on Molecular Docking and Pharmacophore Model." In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2023. http://dx.doi.org/10.1109/bibm58861.2023.10385277.

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Huang, Hung-Jin, Da-Tian Bau, Ming-Hsui Tsai, et al. "Dual-Targeted Drug Design of HER2 and HSP90 by CoMFA Model and Pharmacophore Analysis." In 2009 2nd International Conference on Biomedical Engineering and Informatics. IEEE, 2009. http://dx.doi.org/10.1109/bmei.2009.5305352.

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Levovnik, Bojan D., Aleksa P. Alargić, Miloš M. Svirčev, and Goran I. Benedeković. "Building a 3D QSAR model with isopropylidene analogs of cytotoxic styryl-lactones." In 2nd International Conference on Chemo and Bioinformatics. Institute for Information Technologies, University of Kragujevac, 2023. http://dx.doi.org/10.46793/iccbi23.559l.

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Styryl-lactones are a class of natural products and related analogs that exhibit diverse biological activities, including anticancer, anti-inflammatory, and antimicrobial properties. Since these compounds are routinely obtained in our laboratory from their O-isopropylidene precursors, we envisioned the project to examine and compare their respective structures and in-vitro activities. This paper presents a basic 3D-QSAR steric model built on a small set of 11 selected O-isopropylidene and styryl-lactone (particularly [3.3.0]furofuranone) ligands and their in vitro activities against an MCF-7 c
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Smith, Hudson R., Ryan M. Murphy, Michelle A. Hagenimana, and John A. Allen. "Discovery of agonists for orphan GPR52 using a ligand-based pharmacophore model and virtual screening." In ASPET 2024 Annual Meeting Abstract. American Society for Pharmacology and Experimental Therapeutics, 2024. http://dx.doi.org/10.1124/jpet.294.130118.

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Reports on the topic "Pharmacophore models"

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Hammamieh, Rasha. Apoptosis Use Case: In Silico Evaluation of a Library of Small Molecule Pharmacophore Models for Blocking the Formation of SEB-Major Histocompatibility Class II Complexes. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada482295.

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