Dissertations / Theses on the topic 'In-silico drug design'

Les processus qui mènent à la découverte de nouveaux médicaments sont longs et fastidieux, et les taux de succès sont relativement faibles. L’identification de candidats par le biais de tests expérimentaux s’avère coûteuse, et nécessite de connaître en profondeur les mécanismes d'action de la protéine visée afin de mettre en place des essais efficaces. Le criblage virtuel peut considérablement accélérer ces processus en permettant une évaluation rapide de chimiothèques de plusieurs milliers de molécules afin de déterminer lesquelles sont les plus susceptibles de se lier à une cible. Ces dernières années ont ainsi été témoins de quelques success stories dans ce domaine.Le premier objectif de ce travail était de comparer différents outils et stratégies couramment utilisés dans le criblage virtuel “structure-based”, puis de les appliquer à des cibles protéiques à visée thérapeutique, en particulier dans le cadre du cancer.La protéine kinase GSK3 et un test set de ligands connus ont servi de modèle pour différentes études méthodologiques ayant pour but d’évaluer les programmes de docking et de scoring à notre disposition. En particulier, l’utilisation de plusieurs structures relaxées du récepteur ou l’insertion de torsions sur certains résidus du site actif pendant le docking ont permis d’évaluer l’influence de la flexibilité de la protéine. L’utilité et la pertinence d’outils permettant de générer automatiquement les structures 3D des ligands et de méthodes de consensus scoring ont également été étudiées.Un criblage virtuel de la Pontine, une ATPase impliquée dans la croissance tumorale pour laquelle aucun inhibiteur n’était connu, a permis la sélection de candidats issus de banques de données commerciales. Ces molécules ont été testées dans un essai enzymatique par le biais d’une collaboration, et quatre d’entre elles se sont révélées capable d’inhiber l’activité ATPase de la Pontine. Le criblage de bases de ligands synthétisés et imaginés dans l’équipe a également fourni un inhibiteur original. Au contraire, l’étude de la sPLA2-X humaine, une phospholipase dont l’activité catalytique est dépendante d’un atome de Ca2+ localisé au sein du site actif, a montré les limites de nos outils de docking qui n’ont pas été capables de gérer cet ion métallique et mis en évidence la nécessité de mettre en place d’autres outils
The process of drug discovery is long and tedious. Besides, it is relatively inefficient in terms of hit rate. The identification of candidates through experimental testing is expensive and requires extensive data on the mechanisms of the target protein in order to develop efficient assays. Virtual screening can considerably accelerate the process by quickly evaluating large databases of compounds and determining the most likely to bind to a target. Some success stories have emerged in the field over the last few years.The objectives of this work were first, to compare common tools and strategies for structure-based virtual screening, and second, to apply those tools to actual target proteins implied notably in carcinogenesis.In order to evaluate the docking and scoring programs available, the protein kinase GSK3 and a test set of known ligands were used as a model to perform methodological studies. In particular the influence of the flexibility of the protein was explored via relaxed structures of the receptor or the insertion of torsions on the side chains of residues located in the binding site. Studies concerning the automatic generation of 3D structures for the ligands and the use of consensus scoring also provided insights on the usability of these tools while performing a virtual screening.Virtual screening of the human protein Pontin, an ATPase implied in tumor cell growth for which no inhibitors were known, allowed the prioritization of compounds from commercial databases. These compounds were tested in an enzymatic assay via a collaboration, and led to the identification of four molecules capable of inhibiting the ATPase activity of Pontin. Additional screens of in-house oriented databases also provided at least one innovative inhibitor for this protein. On the contrary, a study of the human PLA2-X, a phospholipase that requires a Ca2+ atom to bind to its active site in order to catalyze the hydrolysis of its substrate, revealed the limits of our docking tools that could not handle the metal ion and the need for new tools

In the last decades, the applications of computational methods in medicinal chemistry have experienced significant changes which have incredibly expanded their approaches, and more importantly their objectives. The overall aim of the present research project is to explore the different fields of the modelling studies by using well-known computational methods as well as different and innovative techniques. Indeed, computational methods traditionally consisted in ligand-based and the structure-based approaches substantially aimed at optimizing the ligand structure in terms of affinity, potency and selectivity. The studies concerning the muscarinic receptors in the present thesis applied these approaches for the rational design of novel improved bioactive molecules, interacting both in the orthosteric (e.g., 1,4-dioxane agonist) and in the allosteric sites. The research includes also the application of a novel method for target optimization, which consists in the generation of the so-called conformational chimeras to explore the flexibility of the modelled GPCR structures. In parallel, computational methods are finding successful applications in the research phase which precedes the ligand design and which is focused on a detailed validation and characterization of the biological target. A proper example of this kind of studies is given by the study regarding the purinergic receptors, which is aimed at the identification and characterization of potential allosteric binding pockets for the already reported inhibitors, exploiting also innovative approaches for binding site predictions (e.g., PELE, SPILLO-PBSS). Over time, computational applications felt a rich extension of their objectives and one of the clearest examples is represented by the ever increasing attempts to optimize the ADME/Tox profile of the novel compounds, so reducing the marked attrition in drug discovery caused by unsuitable pharmacokinetic profiles. Coherently, the first and main project of the present thesis regards the field of metabolism prediction and is founded on the meta-analysis and the corresponding database called MetaSar, manually collected from the recent specialized literature. This ongoing extended project includes different studies which are overall aimed at developing a comprehensive method for metabolism prediction. In detail, this Thesis reports an interesting application of the database which exploits an innovative predictive technique, the Proteochemometric modelling (PCM). This approach is indeed at the forefront of the latest modelling techniques, as it perfectly fits the growing request of new solutions to deal with the incredibly huge amount of data recently produced by the “omics” disciplines. In this context, MetaSar represents an alternative and still appropriate source of data for PCM studies, which also enables the extension of its fields of application to a new avenue, such as the prediction of metabolism biotransformation. In the present thesis, we present the first example of these applications, which involves the building of a classification model for the prediction of the glucuronidation reaction. The field of glucuronidation reactions is exhaustively explored also through an homology modelling study aimed at defining the complete three-dimensional structure of the enzyme UGT2B7, the main isoform of glucuronidation enzymes in humans, in complex with the cofactor UDPGA and a typical substrate, such as Naproxen. The paths of the substrate entering to the binding site and the egress of the product have been investigated by performing Steered Molecular Dynamics (SMD) simulations, which were also useful to gain deeper insights regarding the full mechanism of action and the movements of the cofactor.

1. SUMMARYMyeloperoxidase (MPO) which belongs to the peroxidase family, is found in mammalian neutrophils. This heme enzyme contributes to the production of (pseudo)halogenous acid such as HOCl which oxidizes proteins, cell membrane, DNA and RNA causing death for the pathogens. It has an antimicrobial effect due to HOCl secreting inside the phagosomes of the neutrophils, whereas it will be released outside neutrophils causing oxidative damages for the host tissues. Proteins, lipids, lipoproteins, DNA and RNA are potential targets of the MPO resulting in several chronic syndromes. Many researchers have discovered the harmful effects of MPO and its products demonstrating its role in many inflammatory chronic diseases such as: Cardiovascular diseases as in atherosclerosis. MPO contribution in atherosclerosis development has been demonstrated. Neurodegenerative diseases also was related to MPO: such as Alzheimer’s disease (AD), multiple sclerosis (MSc) and Parkinson’s disease The enzyme has been also pointed out in other diseases such as renal disease and cancer.For these reasons, MPO as a target of drug discovery has attracted the attention of many researchers. X-ray 3D structures were resolved for this enzyme, biological activity and mechanism of action were investigated in depth, and many medicinal chemists have investigated and screened for new MPO inhibitors. Indeed, this cumulative work including X-ray data, the role of MPO in different pathologies, MPO inhibitory mechanism of action, screening and various chemical entities that inhibit MPO, provided sufficient elements to start a new drug design and drug discovery process on MPO.The aim of the present study was to apply a rational drug design approach to the myeloperoxidase inhibition: from in silico to pharmacological activity. This includes:─ Conducting high throughput virtual screening in order to find new potential hits to inhibit MPO followed by mechanism of inhibition determination. ─ Selecting one hit and then implementing a whole pharmacomodulation process in order to increase the potency of the inhibition greater than the starting hit and to improve the selectivity.Firstly, a rational drug design process was launched to find new hits using high throughput virtual screening. The chosen database for the screening was ASINEX database published in ZINC.X-ray structure of human peroxidase complexed to cyanide and thiocyanate (PDB 1DNW) was selected to conduct High-Throughput Virtual Screening (HTVS). Three successive protocols with different levels of accuracy in the docking and scoring processes were used starting with HTVS, followed by Standard Precision (SP) and finally with Xtra Precision (XP). The quality of the docking process performed was validated by docking a set of 60 chosen molecules of varying chemical structure and known as MPO inhibitors. From the result of the HTVS conducted on 1,350,000 compounds, the 100 best compounds were selected. Among them, 81 molecules were available for purchase from ASINEX, those compounds were tested with a MPO inhibition assay. Thirty-two compounds (39 %) were active, but only 8 compounds were selected, featuring different chemical structures with IC50 values ranging between 0.46 ± 0.07 and 12 ± 3 μM. Among these molecules, two compounds were the best and considered as hits. One has purinedione structure which is similar with the structure of thioxanthine derivatives (F9, IC50=0.46±0.07μM). The second compound has a hexahydropyrimidine structure (A1, IC50 = 0.5 ± 0.1 μM) The most common interactions found among all 8 docked ligands are the ionic bond with Glu102 and a stacking (shifted or not) with pyrrole ring D of the prosthetic group. Hydrogen bonds with Glu102, Thr100, Gln91, Arg239, or the propionate groups of the heme are also found in several docked geometries of the complexes. Interestingly, interactions with Glu102 and pyrrole ring D of the heme were also seen with fluorotryptamine derivatives and also salicylhydroxamic acid (SHA).For measuring MPO-dependent LDL oxidation, the two best compounds were tested. Compounds A1 and F9 showed good inhibition on MPO-dependent LDL oxidation (62 ± 6, 4.5 ± 0.9, 11 ± 2% and 11 ± 2, 2.6 ± 0.8, 6 ± 4%, respectively).Consequently, in order to determine the mechanism of inhibition transient-state kinetics were further investigated of all the 8 selected compounds.Both new lead compounds (A1 and F9) act as electron donors of both Compound I and Compound II of MPO. The reaction with Compound I was significantly faster (k2 ≫ k3). As a consequence, the enzyme is trapped in the Compound II state. They reversibly inactivated the enzyme blocking the harmful halogenation activity of MPO by transferring it to the MPO peroxidase cycle. In the present study, 8 active and reversible MPO inhibitors were selected. They act as electron donors of the oxidoreductase and efficiently block the halogenation activity with reversible inactivation. Two of the selected compounds have a submicromolar activity and inhibit MPO-dependent LDL oxidation. The high-throughput virtual screening was proved to be a successful tool to find new leads of MPO inhibitors. Conducting HTVS on a large-scale database enabled selection of novel scaffolds of MPO inhibitors never explored before in less time and at less expenses.Finding 8 new different chemical scaffolds through the first step of this drug discovery process led us to choose a new hit, compound A1, which has a hexahydropyrimidine structure, compound F9 was not chosen despite being more active due to its similarity to compounds discovered by AstraZeneca. To conduct pharmacomodulation, a validation of the docking procedure was conducted by comparing the X-ray structures of MPO with 2-(3,5-bistrifluoromethylbenzylamino)-6-oxo-1H-pyrimidine-5- carbohydroxamic acid, HX1, and SHA in the X-ray structures of human MPO in complex with cyanide and thiocyanate (PDB code 1DNW) as well as in complex with HX1 (PDB code 4C1M). Compound A1 was docked into both target structures 1DNW and 4C1M. In both cases, A1 showed almost the same poses.Based on the binding modes of A1, different strategies were developed for the design of derivatives which were mainly focused on the substitution of the aromatic rings A and B, the 2 amino groups and the side chain bridges.Pharmacomodulation was carried out on the hit A1 with different strategies:─ Investigating the role of hydroxyl groups on both aromatic rings─ Shifting the position of the amino groups in the hexahydropyrimidine ring to obtain piperazine derivatives and introduction of fluorine ─ Eliminating of one ring and of an amino group in the hexahydropyrimidine ring leading to piperidine derivatives ─ Opening the hexahydropyrimidine ring while keeping amine function and changing the length of the bridge between this amino group and aromatic ring as well as the impact of substitutions on aromatic rings.─ Hybridization of fluorotryptamine derivatives (effective MPO inhibitors) with hit A1.Based on of the docking experiments, 37 designed compounds were synthesized. The assessment of inhibition of the chlorination activity of MPO was undertaken over the 37 compounds. The hit A1 IC50 = 500 nM. The best compounds inhibiting MPO exhibited the following characteristics:─ One amino group on the bridge between aromatic rings was sufficient for the establishment of binding to Glu102 ─ The presence of three methylene groups between the secondary amine and an aromatic ring improved the inhibition of chlorination and thus decreased the IC50 values. These results showed that the position of the hydroxyl group is important. The distance between the hydrogen bond acceptor (HBA) group of one aromatic ring and the amino group is very important. The docking experiments of bisarylpropylamine derivatives showed ionic and hydrogen bonding interactions between Glu102 and hydroxyl group on aromatic ring linked to the longer side chain.─ Hybridized compounds which carry a fluorotryptamine instead of the phenol ring obtained by hybridization of hit A1 and the potent MPO inhibitors fluorotryptamine derivatives. Actually, compound 38 (which had one aromatic ring and a propyl bridge attached to indole ring) had an IC50 = 54 nM which was 10 times more powerful than the starting hit.The 3 best compounds were tested to examine the transient kinetics. They act as electron donors of the oxidoreductase and efficiently shift MPO from the chlorination cycle to the peroxidase cycle. Due to the similarity of the best compound 38 to serotonin it was tested with the two other best compounds on serotonin transporter (SERT) to examine the selectivity between MPO and SERT.Compound 38 had higher selectivity over MPO but the best selective compound was 28 that contains two aromatic rings carrying one hydroxyl and one fluorine.Electron density maps were conducted to predict the site of oxidation. Results suggested it occurs preferentially at the benzene ring or the indole ring in the best compounds.Determination of redox potentials for the synthesized compounds were tested. Best compounds act as electron donors allowing a one-electron reduction of Compound I.In conclusion, the present study succeeded through rational drug design including structure-based drug design and HTVS to identify new chemical entities for MPO inhibition. Eight compounds were more active than the starting hit A1 with submicromolar inhibition potency. Hybridization and structure based design also gave improvement of selectivity of inhibitors against MPO such as compound 38. Bis-arylalkylamine derivatives are a new group of MPO inhibitors with higher selectivity which could be a new hit for future development.
Doctorat en Sciences biomédicales et pharmaceutiques (Pharmacie)
info:eu-repo/semantics/nonPublished

Les méthodes de criblage in silico basées sur la structure du récepteur sont utilisées pour faciliter la découverte de nouvelles molécules à visée thérapeutique. En utilisant différents outils de docking/scoring, nous avons optimisé un protocole de criblage hiérarchique développé au laboratoire. Ce nouveau protocole a été validé et optimisé pour différentes protéines aux propriétés structurales et physicochimiques très diverses puis appliqué sur deux cibles ayant un rôle déterminant dans différents cancers, la phosphatase à double spécificité CDC25 et le protéasome 20S. En utilisant des chimiothèques filtrées ADME-tox et préparées pour ces projets, nous avons identifié de nouvelles molécules actives sur ces cibles réputées difficiles. Ces inhibiteurs prometteurs ayant une activité in vitro de l’ordre du micromolaire, actifs sur cellules et possédant des squelettes novateurs et optimisables constitueront une base intéressante pour le développement de nouveaux médicaments à visée antiproliférative
Virtual ligand screening methods based on the structure of the receptor are extensively used to facilitate the discovery of lead compounds. Using different docking/scoring packages, we optimized a hierarchical virtual ligand screening protocol developed in our lab. This new protocol has been validated on different targets with different binding site properties. This multi-step hierarchical protocol has been applied to two targets of therapeutic importance, namely, the dual specificity phosphatase CDC25 and the 20S proteasome. Using ADME-tox filtered compound collections processed in our lab, we identified several new active molecules on these two difficult targets. These promising micromolar inhibitors displaying novel and growable scaffolds can lead to new potential drugs for cancer treatment

G protein-coupled receptors (GPCRs) constitute a very large family of heptahelical, integral membrane proteins that mediate a wide variety of physiological processes, ranging from the transmission of the light and odorant signals to the mediation of neurotransmission and hormonal actions. GPCRs are dysfunctional or deregulated in several human diseases and are estimated to be the target of more than 40% of drugs used in clinical medicine today. The crystal structures of rhodopsin and the recent published crystal structures of beta-adrenergic receptors and human A2A Adrenergic Receptor provide the information of the three-dimensional structure of GPCRs, which supports homology modeling studies and structure-based drug-design approaches. Rhodopsin-based homology modeling has represented for many years a widely used approach to built GPCR three-dimensional models. Structural models can be used to describe the interatomic interactions between ligand and receptor and how the binding information is transmitted through the receptor. Both agonist and antagonist like states can be described by several different conformational receptor states depending on the nature of both ligand and receptor. Considering different complementarities, we might explore different conformations of the same pharmacological state. We investigated the molecular pharmacology of adenosine receptors and, in particular, the human A3 adenosine receptor (hA3AR) by using an interdisciplinary approach to speed up the discovery and structural refinement of new potent and selective hA3AR antagonists. Human A3AR belongs to adenosine receptors family of GPCRs, which consists of four distinct subtypes: A1, A2A, A2B, A3 that are ubiquitously expressed in the human body. The hA3AR, which is the most recently identified adenosine receptor, is implicated in a variety of important physiological processes. Activation of A3ARs increases the release of inflammatory mediators, such as histamine from rodent mast cells, and it inhibits the production of tumor necrosis factor-alpha. The activation of the hA3AR seems to be involved in immunosuppression and in the response to ischemia of the brain and heart. Agonists or antagonists of A3ARs are potential therapeutic agents for the treatment of ischemic and inflammatory diseases. The first model of human A3AR has been built using a conventional rhodopsin-based homology modeling approach. The model has been used to probe atomic level specific interactions, detected using site-directed mutagenesis analysis. The rhodopsin-based model of the hA3AR in its resting state (antagonist-like state) has been revisited, taking into account a novel strategy to simulate the possible receptor reorganization induce by the antagonist-binding. We called this new strategy ligand-based homology modeling (LBHM). It is an evolution of a conventional homology modeling algorithm: any selected atoms will be included in energy tests and in minimization stages of the modeling procedure. Ligand-based option is very useful when one wishes to build a homology model in the presence of a ligand docked to the primary template. Starting from the conventional rhodopsin-based homology model and applying our ligand-based homology modeling implementation we can generate other antagonist-like conformational states of hA3AR in which the ligand recognition cavity is expanded. Using different antagonist-like conformational states, we are able to rationalize the observed activities for all the compounds analyzed. Many severe analysis concerning false-positives and false-negatives situations are usually conducted. To strictly validate this methodology as novel tool to address the multi-conformational space of GPCRs, we have analyzed different classes of known human A3 antagonists in the corresponding putative ligand binding site: for example triazoloquinoxalin-1-one derivatives, arylpyrazolo-quinoline derivatives and pyrazolo-triazolo-pyrimidines derivatives. These studies led to the identification of groups for every class of antagonists that, introduced one by one in a suitable position, afford high hA3AR affinity and good selectivity. Starting from these binding requirements, we decided to perform an in silico molecular simplification approach to identify a suitable fragmentation route of the 4-amino-triazoloquinoxalin-1-one scaffold and explore which of the structural features were essential to guarantee efficient ligand-receptor recognition. With the availability of new three dimensional templates different from rhodopsin, we built new models of hA3AR. All the models were used for a molecular dynamic simulation in a POPC bilayer to investigate the topological fluctuation of the binding pocket.
I recettori accoppiati alle proteine G (GPCR) costituiscono una grande famiglia di proteine integrali di membrana caratterizzate da sette eliche transmenmbrana, che mediano un'ampia gamma di processi fisiologici che vanno dalla trasmissione della luce e dei segnali olfattivi alla mediazione della neurotrasmissione e dell'azione degli ormoni. I GPCR mancano di una corretta regolazione in molte patologie umane ed è stato stimato che costituiscano il target del 40% dei medicinali utilizzati attualmente in clinica. La struttura cristallografica della rodopsina e le strutture più recenti del recettore beta adrenergico e del recettore adenosinico A2A forniscono l'informazione strutturale che sta alla base della costruzione di modelli per omologia e degli approcci di structure-based drug design dei GPCR. La costruzione di modelli di GPCR per omologia basati sulla struttura della rodopsina ha rappresentato per molti anni un approccio ampiamente utilizzato. Questi modelli possono essere usati per descrivere le interazioni interatomiche tra ligando e recettore e come le informazioni sono trasmesse attraverso il recettore. Diversi stati conformazionali del recettore possono essere in grado di descrivere la conformazione del recettore che lega l'agonista e quella che lega l'antagonista, a seconda della natura di ligando e recettore. Se si considerano diverse complementarietà, si possono esplorare diversi stati conformazionali di uno stesso stato farmacologico. Noi abbiamo studiato la farmacologia molecolare dei recettori adenosinici e, in particolare, del recettore adenosinico A3 umano (hA3AR), utilizzando un approccio interdisciplinare al fine di massimizzare la scoperta e l'ottimizzazione strutturale di nuovi antagonisti potenti e selettivi per il hA3AR. Il hA3AR fa parte della famiglia dei recettori adenosinici che consiste in quattro diversi sottotipi (A1, A2A, A2B, A3) che sono espressi in tutto il corpo umano. Il recettore adenosinico A3 è stato identificato più recentemente ed è implicato in importanti processi fisologici. L'attivazione del hA3AR aumenta il rilascio di mediatori dell'infiammazione, come l'istamina dalle mastcellule, e inibisce la produzione del TNF-alpha. L'attivazione del hA3AR sembra essere coinvolta nell'immunosoppressione e nella risposta ischemica di cuore e cervello. Agonisti o antagonisti del hA3AR sono potenziali agenti terapeutici nel trattamento di patologie ischemiche e infiammatorie. Il primo modello di hA3AR è stato costruito usando un approccio convenzionale di homology modeling basato sulla rodopsina ed è nel suo stato che lega l'antagonista. Dopo essere stato utilizzato per verificare le interazioni a livello molecolare che erano state evidenziate da studi di mutagenesi, il modello è stato rivisto prendendo in considerazione una nuova strategia che simula la possibile riorganizzazione del recettore indotta dal legame con l'antagonista. Abbiamo chiamato questa strategia ligand-based homology modeling. E' un'evoluzione dell'algoritmo convenzionale di homology modeling: ogni atomo selezionato viente preso in considerazione nei test energetici e nelle fasi di minimizzazione della procedura di modeling. L'opzione ligand-based è molto utile quando si vuole costruire un modello per omologia in presenza di un ligando nella sua ipotetica conformazione di legame nel templato iniziale. A partire dal modello ottenuto dalla rodopsina e applicando la tecnica del LBHM, possiamo generare altri stati conformazionali del recettore hA3AR che legano l'antagonista, nei quali la cavità di riconoscimento del ligando è espansa. Usando diversi stati conformazionali che legano l'antagonista, possiamo razionalizzare l'attività misurata sperimentalmente di tutti i composti analizzati. Sono condotte severe analisi relative a falsi positivi e falsi negativi. Per validare la metodologia come nuovo strumento per indirizzare lo spazio multiconformazionale dei GPCR, abbiamo analizzato diverse classi di antagonisti con attività nota sul hA3AR: ad esempio derivati triazolo-chinossalinonici, derivati arilpirazolo-chinolinici e derivati pirazolo-triazolo-pirimidinici. Questi studi hanno portato all'identificazione di gruppi per ogni classe di antagonisti che, se introdotti in una precisa posizione, portano ad un'alta affinità e ad una buona selettività per il hA3AR. A partire dalle caratteristiche risultate importanti per il legame, abbiamo applicato una tecnica di semplificazione molecolare in silico per identificare una possibile via di frammentazione della struttura 4-amino-triazolochinoassalin-1-onica ed esplorare quali sono le caratteristiche strutturali essenziali per garantire un'efficiente riconoscimento ligando-recettore. Con la disponibilità di nuove strutture tridimensionali da utilizzare come templati diversi dalla rodopsina, abbiamo costruito nuovi modelli del recettore hA3AR. Tutti i modelli sono stati usati per una simulazione di dinamica molecolare in un doppio strato fosfolipidico, per analizzare le fluttuazioni topologiche della tasca di legame.

Thesis (Ph. D.)--Ohio State University, 2005.
Title from first page of PDF file. Document formatted into pages; contains xvii, 271 p.; also includes graphics. Includes bibliographical references (p. 245-269). Available online via OhioLINK's ETD Center

Proteins are large macromolecules constituted by amino acids that are responsible for most of the biological processes within a cell. Proteins showing high complementary affinity may bind forming protein-protein complexes. In this context, antibodies are proteins that recognize abnormal particles in the body (known as epitopes), and are elicited by means of random recombinatory events followed by strict screening selection processes. Along their production, antibodies can be modified by mutation events leading to potent antibody variants. In this sense, there is an industrial and biomedical interest for the artificial optimization of antibodies. The rise of the computational era together with the deeper understanding of structural biology allowed the design and implementation of predictive algorithms for simulating the effects of mutations in protein-protein complexes. This process usually involves, among others, the prediction of changes in Gibbs free energy upon mutation and the use of other computational simulations for unveiling motions and binding patterns, such as Molecular Dynamics and Monte Carlo techniques. During this thesis, we have developed and implemented predictive algorithms focused on the design of potent antibody variants. We developed UEP, an open-source code for predicting the effects of mutations in protein-protein complexes. UEP differs from the state-of-the-art and employs other sources of knowledge rather than experimental binding affinity determinations upon mutation. Moreover, we designed a PELE protocol to simulate the binding affinity of antibodies against hypermutated HIV-1 viral isolates. Finally, we describe three different computational workflows for antibody optimization. We particularly focused on the challenge of increasing the binding potency of the N6 antibody, one of the best antibodies against HIV-1. Each computational workflow has been evaluated experimentally by our collaborators from Irsicaixa, and such combined computational and experimental effort resulted in the design of an improved variant of the N6 antibody against HIV-1.

Kinases are involved in a multitude of signaling pathways, such as cellular growth, proliferation, and apoptosis, and have been discovered to be important in numerous diseases including cancer, Alzheimer's disease, cardiovascular health, rheumatoid arthritis, and fibrosis. Due to the involvement in a wide variety of disease types, kinases have been studied for exploitation and use as targets for therapeutics. There are many limitations with developing kinase target therapeutics due to the high similarity of kinase active site composition, making the utilization of new techniques to determine kinase exploitability for therapeutic design with high specificity essential for the advancement of novel drug strategies. In silico approaches have become increasingly prevalent for providing useful insight into protein structure-function relationships, offering new information to researchers about drug discovery strategies. This work utilizes streamlined computational techniques on an atomistic level to aid in the identification of orthologue and isoform exploitability, identifying new features to be utilized for future inhibitor design. By exploring two separate kinases and kinase targeting domains, we found that orthologues and isoforms contain distinct features, likely responsible for their biological roles, which can be utilized and exploited for selective drug development. In this work, we identified new exploitable features between kinase orthologues for treatment in Human African Trypanosomiasis and structural morphology differences between two kinase isoforms that can potentially be exploited for cancer therapeutic design.
Master of Science in Life Sciences
Numerous diseases such as cancer, Alzheimer's disease, cardiovascular disease, rheumatoid arthritis, and fibrosis have been attributed to different cell growth and survival pathways. Many of these pathways are controlled by a class of enzymes called kinases. Kinases are involved in almost every metabolic pathway in human cells and can act as molecular switches to turn on and off disease progression. Due to the involvement of these kinases' in a wide variety of disease types, kinases have been continually studied for the development of new drugs. Developing effective drugs for kinases requires an extensive understanding of the structural characteristics due to the high structural similarity across all kinases. In silico, or computational, techniques are useful strategies for drug development practices, offering new information into protein structure-function relationships, which in turn can be utilized in drug discovery advancements. Utilizing computational methods to explore structural features can help identify specific protein structural features, thus providing new strategies for protein specific inhibitor design. In this work, we identified new exploitable features between kinase orthologues for treatment in Human African Trypanosomiasis and structural morphology differences between two kinase isoforms that can potentially be exploited for cancer therapeutic design.

L’inflammation est un phénomène affectant des millions de personnes à travers le monde. Il existe une grande variété de médiateurs inflammatoires impliqués dans différentes fonctions biologiques, dont la cyclooxygénase-2. Bien que de nombreux inhibiteurs sélectifs de la COX-2 aient été développés et commercialisés, ceux-ci présentent des effets secondaires dont la gravité a entraîné, dans certains cas, l'arrêt de leur commercialisation.De nos jours, les méthodes in silico sont de plus en plus employées dans les stratégies de découverte de nouvelles molécules à visée thérapeutique. Au cours de ce projet, nous nous sommes appuyés sur les modèles pharmacophoriques et les méthodes de docking afin de guider et de prioriser la synthèse de molécules de structures diverses et originales, susceptibles de présenter les meilleures affinités pour la cible étudiée. Ainsi, des prédictions réalisées avec le logiciel TOMOCOMD-CARDD combinées à des tests biologiques, ont permis d’identifier le cyclocoumarol comme une molécule potentiellement anti-inflammatoire. Dans le cadre de ces travaux nous nous sommes intéressés à la synthèse et l’étude d’analogues du cyclocoumarol en tant qu’inhibiteurs sélectifs de la COX-2. La pharmacomodulation autour du cyclocoumarol et la mise en place de stratégies de synthèse judicieuses ont permis d’obtenir une série d’analogues. Divers outils bioinformatiques ont été utilisés : le logiciel LigandScout a permis de construire des pharmacophores sélectifs de la COX-2 et les études de docking ont permis de comprendre les modes de liaisons des différents composés. Enfin, le logiciel SeeSAR, a permis de prédire l’affinité des molécules les plus susceptibles d’inhiber sélectivement la COX-2. Les tests biologiques ont confirmé leur activité inhibitrice envers la COX-2 avec une inhibition non significative vis-à-vis de COX-1. Parmi les molécules synthétisées, le 4-OMe cyclocoumarol a démontré une activité et une sélectivité très intéressantes, comparables au NS-398, un inhibiteur sélectif connu de la COX-2. A partir des résultats biologiques obtenus, un travail de phamacomodulation autour de ces dérivés du cyclocoumarol a été réalisé en utilisant des outils in silico dans le but de prédire l’affinité de nouveaux composés et de découvrir de nouveaux inhibiteurs sélectifs de la COX-2.Mots clés : cyclocoumarol, benzalacétones, warfarines, pharmacophores, docking, criblage virtuel, COX-2, repositionnement
Inflammation is a phenomenon affecting millions of people throughout the world. There is a broad range of inflammatory mediators implied in different biological functions including the cyclooxygenase-2. Although many selective inhibitors selective of COX-2 have been developed and marketed, they have displayed diverse side effects leading, in some cases, to their with drawal from the market. Nowadays, in silico methods are more and more used in the drug discovery process. In this project, we have used pharmacophoric models and docking methods to guide and prioritize the synthesis of molecules, presenting different and original structures, with enhanced affinity for the biological target. Thus, predictions realized with the TOMOCOMD-CARDD software together with biological tests enable to identify the cyclocoumarol as a potential anti-inflammatory molecule. As part of these works, the synthesis of and the study of cyclocoumarol analogues as selective inhibitors of COX-2 have been realized. Pharmacomodulation of cyclocoumarol and development of synthesis strategies led to a serie of cyclocoumarol analogues. Several bioinformatics tools have been used: selective COX-2 pharmacophores were elucidated using LigandScout and docking studies (Surflex) were conducted to understand the binding mode of different compounds. Finally, SeeSAR enabled to predict the affinity of the molecules the most susceptible to inhibit selectively COX-2. Biological tests confirmed their inhibitory activity against COX-2 and showed no significant inhibition for COX-1. Among the synthesized molecules, the 4-OMe cyclocoumarol has demonstrated an activity and a selectivity very interesting, similar to NS-398, a known selective COX-2 inhibitor.Based on the biological results obtained, a pharmacomodulation study of cyclocoumarol derivatives has been realized using in silico tools in order to predict the affinity of new compounds and to discover new selective inhibitors of COX-2.Keywords : cyclocoumarol, benzalacetones, warfarines, pharmacophores, docking, virtual screening, COX-2, repositioning

Novel computational strategies are continuously being demanded by the pharmaceutical industry to assist, improve and speed up the drug discovery process. In this scenario chemoinformatics provide reliable mathematical tools to derive quantitative structure-activity relationships (QSARs), able to describe the correlation between molecular descriptors and various experimental profiles of the compounds. In the last years, nonlinear machine learning approaches have demonstrated a noteworthy predictive capability in several QSAR applications, confirming their superiority over the traditional linear methodologies. Particularly the feasibility of the classification approach has been highlighted in solving complex tasks. Moreover, the introduction of the autocorrelation concept in chemistry allows the structural comparison of the molecules by using a vectorial fixed-length representation to serve as effective molecular descriptor. In the present thesis we have deeply investigated the wide applicability and the potentialities of nonlinear QSAR strategies, especially in combination with autocorrelation molecular electrostatic potential descriptors projected on the molecular surface. Our intent is arranged in six different case studies that focus on crucial problems in pharmacodynamics, pharmacokinetics and toxicity fields. The first case study considers the estimation of a physicochemical property, the aqueous solvation free energy, that strictly relates to the pharmacokinetic profile and toxicity of chemicals. Our discussion on pharmacodynamics deals with the prediction of potency and selectivity of human adenosine receptor antagonists (hAR). The adenosine receptor family belongs to GPCR (G protein-coupled receptors) family A, including four different subtypes, referred to as A1, A2A, A2B and A3, which are widely distributed in the tissues. They differentiate for both pharmacological profile and effector coupling. Intensive explorative synthesis and pharmacological evaluation are aimed at discovering potent and selective ligands for each adenosine receptor subtype. In the present thesis, we have considered several pyrazolo-triazolo-pyrimidine and xanthine derivatives, studied as promising adenosine receptor antagonists. Then, a second case study focuses on the comparison and the parallel applicability of linear and nonlinear models to predict the binding affinity of human adenosine receptor A2A antagonists and find a consensus in the prediction results. The following studies evaluate the prediction of both selectivity and binding affinity to A2AR and A3R subtypes by combining classification and regression strategies, to finally investigate the full adenosine receptor potency spectrum and human adenosine receptor subtypes selectivity profile by applying a multilabel classification approach. In the field of pharmacokinetics, and more specifically in metabolism prediction, the use of multi- and single-label classification strategies is involved to analyze the isoform specificity of cytochrome P450 substrates. The results lead to the identification of the appropriate methodology to interpret the real metabolism information, characterized by xenobiotics potentially transformed by multiple cytochrome P450 isoforms. As final case study, we present a computational toxicology investigation. The recent regulatory initiatives due to REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) require the ecotoxicological and risk assessment of chemicals for safety. Most of the current evaluation protocols are based on costly animal experiments. So, chemoinformatic tools are heartily recommended to facilitate the toxicity characterization of chemical substances. We describe a novel integrated strategy to predict the acute aquatic toxicity through the combination of both toxicokinetic and toxicodynamic behaviors of chemicals, by using a machine learning classification method. The goal is to assign chemicals to different levels of acute aquatic toxicity, providing an appropriate answer to the new regulatory requirements. As preliminary validation of our approach, two toxicokinetic and toxicodynamic models have been applied in series to inspect both aquatic toxicity hazard and mode of action of a set of chemical substances with unknown or uncertain toxicodynamic information, assessing the potential ecological risk and the toxic mechanism.
Nuove strategie computazionali vengono continuamente richieste dall'industria farmaceutica per assistere, migliorare e velocizzare il processo di scoperta dei farmaci. In questo scenario la chemoinformatica fornisce affidabili strumenti matematici per ottenere relazioni quantitative struttura-attività (QSAR), in grado di descrivere la correlazione tra descrittori molecolari e vari profili sperimentali dei composti. Negli ultimi anni approcci non lineari di machine learning hanno dimostrato una notevole capacità predittiva in diverse applicazioni QSAR, confermando la loro superiorità sulle tradizionali metodologie lineari. E' stata evidenziata particolarmente la praticabilità dell'approccio di classificazione nel risolvere compiti complessi. Inoltre, l'introduzione del concetto di autocorrelazione in chimica permette il confronto strutturale delle molecole attraverso l'uso di una rappresentazione vettoriale di lunghezza fissa che serve da efficace descrittore molecolare. Nella presente tesi abbiamo studiato approfonditamente l'ampia applicabilità e le potenzialità delle strategie QSAR non lineari, soprattutto in combinazione con i descrittori autocorrelati potenziale elettrostatico molecolare proiettato sulla superficie molecolare. Il nostro intento si articola in sei differenti casi studio, che si concentrano su problemi cruciali nei campi della farmacodinamica, farmacocinetica e tossicologia. Il primo caso studio considera la valutazione di una proprietà fisico-chimica, l'energia libera di solvatazione acquosa, che è strettamente connessa con il profilo farmacocinetico e la tossicità dei composti chimici. La nostra discussione in farmacodinamica riguarda la predizione di potenza e selettività di antagonisti del recettore adenosinico umano (hAR). La famiglia del recettore adenosinico appartiene alla famiglia A di GPCR (recettori accoppiati a proteine G), che include quattro diversi sottotipi, cui ci si riferisce come A1, A2A, A2B e A3, ampiamente distribuiti nei tessuti. Si differenziano sia per profilo farmacologico che per effettore cui sono accoppiati. Le intense sintesi esplorativa e valutazione farmacologica hanno lo scopo di scoprire ligandi potenti e selettivi per ogni sottotipo del recettore adenosinico. Nella presente tesi abbiamo considerato diversi derivati pirazolo-triazolo-pirimidinici e xantinici, studiati come promettenti antagonisti del recettore adenosinico. Quindi, un secondo caso studio si focalizza sul confronto e l'applicabilità in parallelo di modelli lineari e non lineari per predire l'affinità di legame di antagonisti del recettore adenosinico A2A umano e trovare un consenso nei risultati di predizione. Gli studi successivi valutano la predizione sia della selettività che dell'affinità di legame ai sottotipi A2AR e A3R combinando strategie di classificazione e regressione, per studiare infine il completo spettro di potenza del recettore adenosinico e il profilo di selettività per i sottotipi hAR mediante l'applicazione di un approccio di classificazione multilabel. Nel campo della farmacocinetica, e più specificamente nella predizione del metabolismo, è coinvolto l'uso di strategie di classificazione multi- e single-label per analizzare la specificità di isoforma di substrati del citocromo P450. I risultati conducono all'identificazione della metodologia appropriata per interpretare la reale informazione sul metabolismo, caratterizzata da xenobiotici potenzialmente trasformati da multiple isoforme del citocromo P450. Come caso studio finale, presentiamo un'indagine in tossicologia computazionale. Le recenti iniziative regolatorie dovute al REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) richiedono l'accertamento ecotossicologico e del rischio dei composti chimici per la sicurezza. La maggiorparte dei correnti protocolli di valutazione è basata su costosi esperimenti animali. Così, gli strumenti chemoinformatici sono caldamente raccomandati per facilitare la caratterizzazione della tossicità di sostanze chimiche. Noi descriviamo una nuova strategia integrata per predire la tossicità acquatica acuta attraverso la combinazione di entrambi i comportamenti tossicocinetico e tossicodinamico dei composti chimici, utilizzando un metodo di classificazione machine learning. L'obbiettivo è assegnare i composti chimici a diversi livelli di tossicità acquatica acuta, fornendo un'appropriata risposta alle nuove esigenze regolatorie. Come validazione preliminare del nostro approccio, due modelli tossicocinetico e tossicodinamico sono stati applicati in serie per esaminare sia il rischio di tossicità acquatica che il modo d'azione di un set di sostanze chimiche con informazione tossicodinamica sconosciuta o incerta, valutandone il potenziale rischio ecologico ed il meccanismo tossico.

L’hepatitis B crònica és una infecció hepàtica causada pel virus de l’hepatitis B (VHB). Tot i la disponibilitat d'una vacuna profilàctica, la infecció pel VHB continua sent un greu problema de salut mundial amb més de 250 milions de portadors a tot el món. Actualment, la infecció pel VHB es tracta amb anàlegs de nucleòs(t)id (NUC) i amb teràpia basada en interferó (IFN-α), que no proporcionen una cura útil. Per tant, hi ha una necessitat significativa de noves teràpies destinades a l’erradicació completa del virus dels hepatòcits infectats. Recentment s’ha reconegut que les molècules petites que actuen com moduladors d’assemblatge de la càpside (CAM) són agents antivirals prometedors per curar la infecció crònica per VHB. El projecte VIRO-FLOW té com a objectiu la identificació d’agents curatius nous contra el VHB, integrant els avantatges de la química de flux continu amb tecnologies de bioassaig in vitro mitjançant microfluídica. L’objectiu final del present projecte de tesi és la creació d’un sistema per a la generació de dades de relació estructura-activitat (SAR), on es poguessin utilitzar un conjunt de tècniques computacionals per accelerar el procés d’identificació de hits/leads, per optimitzar l’eliminació de propietats farmacològiques indesitjables de compostos actius coneguts i guiar la síntesi de llibreries de compostos, tant per batch com per flux continu. El disseny de molècules assistit per mètodes computacionals innovadors, com el cribratge virtual, scaffold hopping, el disseny in silico de biblioteques dirigides i els estudis d’acoblament molecular, adoptats en aquest treball d’investigació van conduir a la identificació de noves biblioteques de CAM per a HBV. També es va desenvolupar un mètode eficient per a la síntesi de compostos amb estructura basada en [1,2,4]triazolo[1,5-a]piridina-2-carboxamida mitjançant flux continu amb l'ajut de càlculs DFT per dilucidar el mecanisme del procés.
La hepatitis B crónica es una infección hepática causada por el virus de la hepatitis B (VHB). A pesar de la disponibilidad de una vacuna profiláctica, la infección por VHB sigue siendo un problema de salud mundial grave. Actualmente, la infección por VHB se trata con análogos de nucleós(t)idos (NUC) y con terapia basada en interferón (IFN-α), que no proporcionan una cura útil. Por tanto, existe una necesidad significativa de desarrollar nuevas terapias destinadas a la erradicación completa del virus de los hepatocitos infectados. Las moléculas pequeñas que actúan como moduladores de ensamblaje de la cápside (CAM) se han reconocido como agentes antivirales prometedores para curar la infección crónica por VHB. El proyecto VIRO-FLOW tiene como objetivo la identificación de nuevos agentes curativos para el VHB, integrando las ventajas de la química de flujo continuo con tecnologías de bioensayos in vitro en microfluídica. El objetivo final del presente proyecto de tesis fue la creación de un sistema para la generación de datos de relación estructura-actividad (SAR), donde se podría utilizar un conjunto de técnicas computacionales para acelerar el proceso de identificación de hits/leads, para optimizar la eliminación de las propiedades farmacológicas indeseables de los compuestos activos conocidos y guiar la síntesis de quimiotecas de compuestos en batch o en flujo continuo. El diseño de moléculas asistido por métodos computacionales innovadores, que incluyen la detección virtual, scaffold hopping, el diseño in silico de quimiotecas dirigidas y los estudios de acoplamiento molecular, adoptados en este trabajo de investigación, llevaron a la identificación de nuevas quimiotecas de CAM del VHB. También se ha desarrollado un método eficaz para la síntesis de compuestos con estructura basada en [1,2,4]triazolo[1,5-a]piridina-2-carboxamida mediante flujo continuo y con la ayuda de cálculos DFT para dilucidar el mecanismo del proceso.
Chronic hepatitis B is a severe liver infection caused by Hepatitis B Virus (HBV). Despite the availability of a prophylactic vaccination since 1982, HBV infection still remains a serious global health issue with more than 250 million carriers worldwide. Currently, HBV infection is treated with nucleos(t)ide analogs (NUCs) and, less commonly, interferon-based therapy (IFN-α). However, the standard of care (SOC) does not provide a functional cure. Thus, there is a significant need for novel therapeutics aiming towards the complete eradication of the virus from infected hepatocytes. Small-molecule capsid assembly modulators (CAMs) have been recently recognized as promising antiviral agents for curing chronic HBV infection. The VIRO-FLOW project aims at the fast and efficient identification of novel curative agents for HBV, integrating the advantages of continuous flow chemistry with in vitro microfluidic bioassay technologies. The end objective of the present thesis project was the creation of an integrated system for the generation of structure-activity relationship (SAR) data, where a suite of computational techniques could be utilized to speed up the process of hit/lead identification, to optimize out undesirable pharmacological properties of known actives and to guide and support the synthesis of compound libraries either in batch or flow. State of the art computer-aided design approaches, including virtual screening, scaffold hopping, in silico focussed library design and molecular docking studies of potential active compounds, adopted in this research work led to the identification of novel libraries of HBV CAMs. Moreover, an efficient method for the synthesis of the [1,2,4]triazolo[1,5-a]pyridine-2-carboxamide scaffold was also developed in continuous flow with the aid of DFT calculations to elucidate the mechanism of the process.

Les interactions protéine-protéine (IPP) jouent un rôle crucial dans de nombreuses voies biologiques et sont de plus en plus explorées en tant que cibles thérapeutiques potentielles, notamment pour le traitement des maladies infectieuses. Cependant, la conception de petites molécules modulatrices pour les IPP reste un défi, car les interfaces des IPP n'ont pas évolué pour lier des petites molécules comme les cibles thérapeutiques conventionnelles telles que les enzymes ou les récepteurs membranaires. Par conséquent, la preuve de leur drugabilité doit être apportée au cas par cas. Dans ce contexte, les approches computationnelles peuvent être utiles pour aider à la conception de modulateurs IPP. Ce travail vise à développer de nouveaux protocoles de conception de médicaments in silico spécifiquement adaptés aux cibles IPP, dans le but de concevoir de nouveaux médicaments antiviraux contre deux cibles IPP : le virus respiratoire syncytial (VRS) et le SARS-CoV-2
Protein-Protein interactions (PPI) play crucial roles in many biological pathways and are being increasingly explored as potential therapeutic targets, including for treating infectious diseases. However, designing small molecule modulators for PPI remains challenging as PPI interfaces have not evolved to bind small molecules like conventional drug targets such as enzymes or membrane receptors. Therefore, proof of their druggability must be made on a case-by-case basis. In this context, computational approaches can be useful in assisting the design of PPI modulators.This work aims to develop new in silico drug design protocols specifically tailored to PPI targets, with the goal of designing new antiviral drugs against two PPI targets: the respiratory syncytial virus (RSV) and the SARS-CoV-2

A proteína hnRNP K é conhecida por seu papel nos múltiplos processos que compõe a expressão gênica, incluindo funções nos estágios de splicing, transcrição e tradução, desempenhadas, principalmente, através da ligação de seus domínios KH a nucleotídeos. A ativação inadequada da hnRNP K tem relação direta com a gênese de alguns tipos de câncer, sobretudo de cabeça e pescoço, mama e colo-retal, evidenciando a mesma como um atrativo alvo molecular para o desenvolvimento de novos fármacos antineoplásicos. Com o auxílio de técnicas in silico, foram identificados dois compostos orgânicos, um derivado de benzimidazol e outro derivado de fenilbenzamida, capazes de impedir a ligação da proteína hnRNP K a oligonucleotídeos in vitro. Aliando as técnicas de docking, campos de interação e dinâmica molecular foi possível sugerir que tais compostos apresentam características estruturais que permitem a realização de interações na fenda de ligação do domínio KH3, principalmente com os resíduos R40 e R59, os quais são considerados chaves no reconhecimento molecular de nucleotídeos. Os derivados de benzimidazol e fenilbenzamida constituem novos compostos de partida na busca de novos antineoplásicos que tem como alvo a proteína hnRNP K. Do ponto de vista de metabolismo e toxicidade, o derivado de fenilbenzamida parece ser mais promissor quando se investiga uma molécula para aplicação terapêutica, uma vez que gerou poucos alertas críticos de toxicidade, ao contrario do derivado de benzimidazol, que apresenta maior potencial genotóxico. Apesar de se ligarem aos domínios KH da hnRNP K e impedir sua complexação a nucelotídeos, ensaios com culturas de células mostraram apenas tênue atividade antitumoral para tais compostos, com maior redução de viabilidade celular, ao redor de 18% a 8,4 M, exibida pelo derivado de fenilbenzamida. Seguindo o princípio do análogo ativo, simulações de triagem virtual na busca de análogos dos ligantes da hnRNP K revelaram 21 novos derivados de benzimidazol ou fenilbenzamida na base de dados EXPRESS-Pick, dos quais 5 foram testados in vitro com a proteína e 3 novos ligantes identificados. Com o intuito de otimizar tais derivados, foram sugeridos in silico substituintes (potenciais bioisósteros) para os anéis dioxopirrolidínicos dos ligantes já identificados, guiando, assim, a futura síntese de novas substâncias com potencial atividade antitumoral. Além disso, o trabalho foi complementado através da proposição de síntese de novos derivados benzoxazepínicos acoplados a purinas, os quais também tem aplicação como antineoplásicos, entretanto por mecanismos que não envolvem a hnRNP K. A grande limitação desses derivados é a presença de um grupo nitro aromático, o qual é reconhecido por sua toxicidade pronunciada. Com o intuito de otimizar tais derivados, foram sugeridos in silico potenciais bioisósteros capazes de substituir o grupo nitro e guiar a síntese e novos derivados com atividade antitumoral e toxicidade reduzida.
hnRNP K protein is known for its role in the multiple processes that compose gene expression, including functions during splicing, transcription and translation, developed, mainly, by the binding of nucleotides to KH domains. Inadequate activation of hnRNP K induces the development of some types of cancer, including head and neck, breast and colorectal. In this way, hnRNP K is an attractive molecular target for antineoplastic drug design. Using in silico strategies, we have identified two organic compounds, a benzimidazole and a phenylbenzamide derivatives, able to prevent the natural binding of nucleotides to hnRNP K in vitro. Applying docking, molecular interaction fields and molecular dynamics simulations it was possible to propose that such compounds present structural characteristics capable to support intermolecular interactions inside KH3 domain binding cleft, mainly with R40 and R59 residues, which are extremely important during molecular recognition of nucleotides by hnRNP K. The benzimidazole and phenylbenzamide derivatives identified are novel lead compounds that can guide the design of new antineoplastic drugs targeting hnRNP K. Considering metabolic and toxicity predictions, the phenylbenzamide seems to be more promising than the benzimidazole derivative as a drug, once the benzimidazole presents genotoxic potential. Although both derivatives prevent the binding of nucleotides to hnRNP K, biological assays with tongue cancer cell lines revealed only a mild antitumoral activity for such compounds. Higher level of cell viability reduction, 18% at 8.4 M, was observed for the phenylbenzamide derivative. Following the similarity principle, virtual screening simulations were made intending to find novel benzimidazole and phenylbenzamide derivatives inside EXPRESS-Pick database. The search revealed 21 compounds, 5 of which were tested in vitro with hnRNP K, where 3 of them were active. Intending to optimize benzimidazole and phenylbenzamide derivatives in order to design more potent chemical entities, we have suggested in silico substituents as potential bioisosteric groups of the dioxopyrrolidine rings of hnRNP K ligands, guiding the future synthesis of novel compounds with enhanced antitumoral activity. Moreover, complementary work proposition was performed through the synthesis of benzoxazepin-purines, which also present antitumoral activity but not through hnRNP K pathway. The major limitation of such derivatives is the presence of a nitro aromatic group, which can be very toxic. 20 potential bioisosteric groups were proposed as fragment candidates to replace the nitro one in order to design novel antitumoral derivatives with reduced toxic potential.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
Cancer is a group of diseases characterized by uncontrolled cell proliferation as a result of epigenetic changes, genetic mutations and accumulated mutations over the time. Tumor cells can invade other tissues in the body in a process called metastasis, significantly worsening the patient's prognosis. In Brazil, for the biennium 2014/2015 are expected 576,000 new cases and around the world, according to WHO, 27 million new cancer cases are expected in 2030 and 17 million deaths from the disease. The antiapoptotic proteins, members of Bcl-2 family proteins, are essential for the survival of tumor cells, even when there are cell death stimuli. In this study were compiled, integrated and prepared the largest publicly available data sets containing biological activity data against the antiapoptotic protein Bcl-xL. Robust and predictive pharmacophore models and QSAR models in line with the OECD recommendations were generated. The pharmacophore models discriminated active and inactive structures with a rate of 0.68-0.92 of success and QSAR models discriminated active and inactive structures at a rate of 0.89-0.93 of success. NCI 2014 dataset was carefully prepared to be submitted to the virtual screening process in which the best pharmacophore model was used as molecular filter. Among the 280 thousand compounds in NCI dataset, 1407 compounds passed to the next stage in which the best consensus QSAR model was used to predict their activity. In the end, the top 50 compounds were selected for purchase and proceed to experimental evaluation as potential candidates for antiapoptotic protein Bcl-xL inhibitors.
Câncer é um grupo de doenças caracterizadas pela proliferação celular descontrolada como resultado de alterações epigenéticas, genéticas e mutações acumuladas ao longo do tempo. Células tumorais podem invadir outros tecidos no organismo em um processo chamado metástase, agravando consideravelmente o prognóstico do paciente. No Brasil, para o biênio de 2014/2015 são esperados 576 mil novos casos e, em todo o mundo, segundo a OMS, são esperados 27 milhões de novos casos de câncer no ano de 2030 e 17 milhões de mortes pela doença. As proteínas antiapoptóticas da família Bcl-2 são fundamentais para a sobrevida das células tumorais, uma vez que as mantém funcionais mesmo frente a estímulos de morte celular. Neste estudo foram compilados, integrados e preparados os maiores conjuntos de dados disponíveis publicamente contendo registros de atividade biológica contra a proteína antiapoptótica Bcl-xL. Modelos farmacofóricos robustos e preditivos bem como modelos de QSAR em consonância com as recomendações da OECD foram gerados. As taxas de acerto dos modelos farmacofóricos discriminaram estruturas ativas de inativas com taxa de 0,68-0,92 de sucesso e os modelos de QSAR discriminaram estruturas ativas e inativas com taxa de 0,89-0,93 de sucesso. A série de dados NCI 2014 foi preparada cuidadosamente para ser submetida ao processo de triagem virtual, no qual foi usado o melhor modelo farmacofórico como filtro molecular. Dentre os 280 mil compostos presentes na série de dados do NCI, 1407 compostos passaram para a etapa seguinte, na qual o melhor modelo consenso de QSAR foi usado para predizer as atividades dos compostos. Ao final, os 50 melhores compostos foram selecionados para serem adquiridos e prosseguirão para avaliação experimental como potenciais candidatos a inibidores da proteína antiapoptótica Bcl-xL.

Kaposi’s sarcoma-associated herpesvirus, is a double-stranded DNA γ - herpesvirus and the main causative agent of Kaposi’s sarcoma (KS). γ - herpesviruses undergo both lytic and latent replication cycles; and encode proteins that modulate host transcription at the RNA level, by inducing decay of certain mRNAs. Here we describe a mechanism that allows the viral endo-/exonuclease SOX to recognise mRNA targets on the basis of an RNA motif and fold. To induce rapid RNA degradation by subverting the main host mRNA degradation pathway SOX was shown to directly bind Xrn1. This may shed light as to how some viruses evade the host antiviral response and how mRNA degradation processes in the eukaryotic cell are involves in this.

Le choix des molécules à tester joue un rôle essentiel dans le succès d'un criblage destiné à identifier de nouveaux composés bioactifs. Les deux étapes importantes dans la préparation des molécules pour le criblage sont le choix de l'espace chimique à considérer et la sélection des molécules pertinentes dans cet espace.
Idéalement la préparation des composés destinés au criblage devrait se faire grâce à un logiciel dédié à cette problématique. Il n'existe cependant aucun logiciel qui soit complètement adapté. Nous avons donc entrepris le développement d'un logiciel de ce type : ScreeningAssistant.
Ce logiciel s'appuie sur un système de gestion de bases de données et permet de créer et de maintenir à jour des chimiothèques de plusieurs millions de molécules uniques provenant de fournisseurs différents. Il permet également de filtrer les structures, en éliminant les molécules potentiellement problématiques ou avec des probabilités d'activités faibles, et de sélectionner un ensemble de composés divers.
Ce logiciel a été utilisé pour l'analyse d'une base de 5 millions de références provenant de 38 fournisseurs de produits chimiques. La proportion de composés uniques, originaux, « drug-like », « lead-like », et divers ont été comparés. La diversité a été étudiée en utilisant des notions différentes, et un score de diversité globale, prenant en compte la diversité suivant les différents critères, a été proposé.
Différentes applications de sélection de composés pour le criblage sont présentées. Ces applications utilisent le programme ScreeningAssistant et d'autres algorithmes développés pour résoudre certains problèmes particuliers.

Os estrógenos exercem importantes efeitos fisiológicos através dos dois subtipos dos receptores de estrógeno humanos (hERs), alfa (hER?) e beta (hER?). Enquanto hER? é um importante alvo macromolecular no desenvolvimento de fármacos para o tratamento do câncer de mama, hER? é um alvo promissor no desenvolvimento de agentes terapêuticos para a terapia de reposição hormonal. O progresso no planejamento de moduladores apresentando maior potência, afinidade e seletividade, entretanto, requer a otimização múltipla de interações intermoleculares fármaco-receptor. A Química Medicinal moderna, de forte caráter multidisciplinar, fornece um arsenal de alternativas e estratégias úteis no processo de planejamento de novos fármacos. As ferramentas de modelagem molecular e de estudos das relações quantitativas entre a estrutura e atividade (QSAR) estão integradas a esse processo, sendo de extremo valor na busca por moléculas bioativas com propriedades múltiplas otimizadas. Para a realização deste trabalho, conjuntos padrões de dados foram organizados para diferentes classes químicas de potentes moduladores dos ERs. Esses conjuntos padronizados para os subtipos do hER, contendo a informação qualificada sobre a estrutura química dos ligantes associada a medida da propriedade farmacológica correspondente, estabeleceram as bases para o desenvolvimento de modelos empregando os métodos holograma QSAR, CoMFA e GRID/PCA. Os modelos finais de HQSAR e CoMFA possuem elevada consistência interna e externa, apresentando bom poder de correlação e predição das propriedades alvo. Juntamente com as informações obtidas pelos mapas de contribuição 2D e de contorno 3D, os modelos de QSAR e GRID/PCA construídos são guias químico-medicinais úteis no planejamento de novos moduladores seletivos do ER possuindo maior afinidade e potência.
Estrogens exert important physiological effects through two human estrogen receptor subtypes (hERs), alpha (hER?) and beta (hER?). While hER? is a macromolecular target of great importance for breast cancer therapy, hER? is an attractive drug target for the development of novel therapeutic agents for hormone replacement therapy. Progress towards the design of modulators having improved potency, affinity and selectivity requires the optimization of multiple ligand-receptor interactions. The strong multidisciplinary character of modern Medicinal Chemistry supplies a rich arsenal of useful rational strategies for the design of new drug candidates. Molecular modeling tools and quantitative structure-activity relationships (QSAR) are integrated into the drug design process in the search of bioactive molecules having optimized properties. In this study, standard data sets were organized for different chemical classes of ER modulators, integrating the qualified information about chemical structure associated to the corresponding pharmacological property. The data sets established the scientific basis for the development of models employing the hologram QSAR, CoMFA and GRID/PCA methods. The final HQSAR and CoMFA models possess high internal and external consistency, with good correlative and predictive power. The generated QSAR and GRID/PCA models as well as the information gathered from the 3D contour maps provide useful guidelines for the design of new selective ER modulators having improved affinity and potency.

The organic cation transporters (OCTs) play a critical role in the absorption, distribution and elimination of many drugs, hormones, herbal medicines, and environmental toxins. Given the broad substrate specificity of OCTs, they fall victim to the high susceptibility for contributing to harmful drug-drug interactions. Further defining how human (h)OCTs mechanistically bind to its broad array of substrates will provide significant insight to the understanding and prediction of drug-drug interactions in polypharmacy patients and the advancement of future rational drug design for therapeutics targeting OCTs. The goal of the current study was to elucidate the critical amino acid residues for transporter-substrate binding interactions on human (h)OCT1 and 2 utilizing in silico molecular modeling techniques (homology modeling and automated docking), as well as in vitro mutagenesis and kinetic transport experiments. Three-dimensional homology models were generated for hOCT1 and 2 using Piriformospora indica phosphate transporter (PiPT) serving as template. A putative binding pocket was identified and used to dock the prototypical substrate MPP+. Docking studies revealed five residues for each transporter (hOCT1 and hOCT2) that may be critical for substrate-transporter interactions. The in silico data was used to guide subsequent in vitro site-directed mutagenesis and kinetic analysis. Four hOCT1 mutants (Gln241Lys, Thr245Lys, Tyr361Ala, and Glu447Lys) and three hOCT2 mutants (Gln242Lys, Tyr362Phe, and Tyr362Ala) showed complete loss of MPP+ transporter activity. Decreased affinity for MPP+ was observed for Phe244Ser and Thr245Ser in hOCT1, and Tyr245Ala in hOCT2. All amino acid residues highlighted in the in vitro experiments may be potentially critical for substrate-transporter interactions particularly Tyr361, Phe244 and Thr245 in hOCT1; and Tyr362 and Tyr245 in hOCT2. Docking of known structurally divergent hOCT1 and hOCT2 substrates revealed similar binding interactions as that identified for MPP+, albeit with some unique residues, suggesting the presence of a large central cavity within both transporters. Through the combination of in silico and in vitro experiments, a putative binding pocket was defined and several residues important for substrate-transporter interaction were identified and verified for hOCT1 and hOCT2. Further defining how OCTs biochemically interact with their broad array of substrates will provide significant insight to the understanding and prediction of drug-drug interactions in polypharmacy patients and the advancement of future rational drug design for therapeutics targeting OCT1 and OCT2.

Inhibition of deoxyuridine triphosphate dUTPase, a ubiquitous enzyme and 'first line' of defence against misincorporation of uracil into DNA, is lethal in E. coll, S. cerevisiae and is also probably in a variety of other organisms including, Plasmodium spp., the causative agent of malaria. dUTPase is a potential chemotherapeutic target. An assortment of molecular modelling tools was used to take advantage of the available structural information to identify differences between the human and protozoan dUTPase enzymes. A major objective of this study was to develop, rationally, the available lead compounds into antimalarial drug candidates. Starting from the crystal structure of a cyclic nucleoside derivative bound to P. falciparum dUTPase, structural models for the interaction of a library of analogues with the dUTPase receptor were generated by automated computational docking. The obtained complexes were evaluated for their consistency using quantitative structure-activity relationship analysis. A comparison between the calculated interaction free energies and experimental biological activities was also made. All the possible interactions of the investigated compounds at the active site and probable ligand binding conformations provided an improved basis for structure-based rational ligand design. Based on docking results, a successful R2 0.80 model for prediction of binding affinities was developed using the linear interaction energy method LIE. In addition, three-dimensional Quantitative Structure-Activity Relationship studies 3D-QSAR generated using the CoMFA methodology yielded highly predictive models R2 0.99 and q2 0.74. Extensive use of this set of molecular modelling methodologies docking, GRID, LIE, 3D-QSAR has allowed for the development of models, which were employed successfully to introduce the available structural information early into the development of antimalarial drugs. This has resulted design of new inhibitors and has opened up a variety of new chemistry projects. In addition, some work was carried out for the development of a predictive in silico model Volsurf for the passive blood brain barrier BBB permeation of compounds.

L’hepatitis B és una infecció hepàtica greu, i la principal causa de càncer de fetge, causada pel virus de l’hepatitis B (VHB). Tot i que hi ha disponible una vacuna profilàctica, l’hepatitis B continua sent un problema de salut greu. Actualment, les teràpies antivirals aprovades per la FDA es limiten a Interferons de tipus 1 i anàlegs de nucleòs(t)id que redueixen els nivells d’antigen del VHB. En els darrers anys, s’ha identificat una nova classe de compostos anomenats moduladors d’assemblatge de la càpside (CAM) com a agent antiviral, que mostren el potencial d’eliminar eficientment l’ADN del VHB de les cèl·lules hepàtiques infectades. L’objectiu d’aquesta tesi doctoral és el desenvolupament de metodologies innovadores, en fluix continu i impulsades computacionalment, per accelerar el descobriment de nous inhibidors del VHB dins del projecte VIRO-FLOW. Aquests nous processos van facilitar l’obtenció de components d’interès en el desenvolupament d’un nou quimiotip de compostos CAM. A més, també s’ha desenvolupat una ruta eficient per sintetitzar [1,2,4]triazolo-[1,5-a]-piridina-2-carboxamides en flux continuo. S'ha avaluat les limitacions de la reacció i s’ha proporcionat un mecanisme de la reacció mitjançant càlculs DFT. A més, s’han dissenyat i optimitzat rutes sintètiques que combinen processos batch i flux continu per obtenir una nova quimioteca. Mitjançant un estudi de la relació estructura-activitat,
La hepatitis B es una infección hepática grave, y la principal causa de cáncer de hígado, causada por el virus de la hepatitis B (VHB). Aunque se dispone de una vacuna profiláctica, la hepatitis B sigue siendo un problema de salud grave. Actualmente, las terapias antivirales aprobadas por la FDA se limitan a Interferones de tipo 1 y análogos de nucleós(t)idos que reducen los niveles de antígeno del VHB. Recientemente, se ha identificado una nueva clase de compuestos denominados moduladores de ensamblaje de la cápside (CAM) como agente antiviral, que muestra el potencial de eliminar eficazmente el ADN del VHB de las células hepáticas infectadas. El objetivo de esta tesis doctoral es el desarrollo de metodologías novedosas, en flujo continuo y computacionalmente impulsadas, para acelerar el descubrimiento de nuevos inhibidores del VHB dentro del proyecto VIRO-FLOW. Estos nuevos procesos facilitaron la obtención de componentes de interés en el desarrollo de un nuevo quimiotipo de compuestos CAM. Además, también se ha desarrollado una ruta eficaz para sintetizar [1,2,4]triazolo- [1,5-a]-piridina-2-carboxamidas en flujo continuo. Se evaluaron las limitaciones de la reacción y se ha proporcionado una mecanismo de la reacción mediante cálculos DFT. Además, se diseñaron y optimizaron rutas sintéticas que combinan procesos batch y flujo continuo para obtener una nueva quimioteca. Mediante un estudio de la relación estructura-actividad y se identificaron dos compuestos lead. Por otro lado, se creó un método de cribado virtual que combina modelos de farmacóforos y el acoplamiento molecular para priorizar la síntesis de nuevos compuestos, dando como resultado nuevos análogos con mayor actividad que el lead inicial. Finalmente, se utilizó una combinación de dinámica molecular y modelos de farmacóforos para realizar un gran cribado virtual. El método condujo a la selección de treinta moléculas con una excelente relación con fármacos antivirales que serán posteriormente evaluados.
Hepatitis B is a serious liver infection and the primary cause of liver cancer caused by Hepatitis B Virus (HBV). Even though a prophylactic vaccine is available, Hepatitis B remains as a serious health issue. Currently, FDA-approved antiviral therapies are limited to type 1 interferons and nucleos(t)ide analogues which reduce HBV antigen levels. In recent years, a new class of compounds named capsid assembly modulators (CAMs) have been identified as antiviral agent, showing the potential to efficiently eliminate HBV DNA from infected liver cells. This doctoral thesis objective are the development of novel methodologies, in continuous flow and computationally driven, that will support and accelerate the discovery of new HBV inhibitors within the VIRO-FLOW project. These new processes facilitated the obtention of several building blocks of interest in the development of a new HBV CAMs chemotype. Furthermore, an efficient route for the synthesis of 1,2,4-triazolo-[1,5-a]-pyridine-2-carboxylate in continuous flow has been also developed. The limitations of the reaction were assessed, and an acute mechanistic understanding of the reaction process was afforded by DFT calculations. Moreover diversity-oriented synthetic routes combining batch and flow processes were designed and optimized to obtain a focused library of a new compound series. A structure-activity relationship study was conducted, and two compounds were identified as potential lead. On another hand, a virtual screening workflow combining pharmacophore modelling and molecular docking was created to prioritize the synthesis of new analogues in compound series under development, resulting in new analogues with higher activity than the initial lead. Finally, a combination of molecular dynamics and pharmacophore modelling was used to conduct a large virtual screening (ca. 65 million compounds). The method led to the selection of thirty molecules with excellent antiviral drug-likeness to be further evaluated.

Sukcinimidi su jedinjenja koja pokazuju višestruke farmakološke efekte uključujući i antiproliferativnu aktivnost, zahvaljujući prisustvu farmakofore sa dva hidrofobna regiona i dva regiona bogata elektronima. Savremeni dizajn lekova ima za cilj da se modifikacijama u strukturi (promena vrste, položaja i orijentacije supstituenata) i in silico računarskim metodama predvide i optimizuju farmakokinetske osobine i bezbednosni profil kandidata za lek. U ranoj fazi razvoja lekova se koriste postojeće baze podataka o molekulskim, farmakokinetskim i toksikološkim parametrima već ispitanih jedinjenja i pomoću matematičkih modela i algoritama predviđaju se osobine novih molekula, eliminišu se neodgovarajući kandidati i postiže se ušteda u vremenu i materijalnim sredstvima. Da se ispitaju fizičko-hemijske karakteristike 11 novosintetisanih metil-etil-N-aril-sukcinimida na osnovu strukture, primenom različitih softverskih paketa; da se na osnovu strukture odrede farmakokinetski i toksikološki parametri, primenom različitih softverskih paketa; da se ispita retenciono ponašanje, odnosno odrede retencione konstante za svako jedinjenje primenom visokoefikasne hromatografije na tankom sloju (HP-TLC) i ispita mogućnost primene retencionih konstanti kao mere lipofilnosti ispitivanih jedinjenja; da se ispita antiproliferativna aktivnost na odabranim kulturama ćelija karcinoma i na zdravim ćelijama fibroblasta pluća; da se analizom molekulskog dokinga ustanovi vezivanje za estrogene receptore. Ispitano je retenciono ponašanje 11 novosintetisanih derivata sukcinimida primenom visokoefikasne hromatografije na tankom sloju (HP-TLC) obrnute faze uz primenu dvokomponentne smeše vode i organskog rastvarača (metanola, acetonitrila ili acetona), sa odgovarajućim zapreminskim udelom organskog rastvarača kao mobilne faze. Iz razvijenih hromatograma su izračunate retencione konstante RM0 i S. Logaritam podeonog koeficijenta (logP) određen je in silico, korišćenjem različitih računarskih programa. In silico su određene fizičko-hemijske karakteristike, farmakokinetski parametri, toksikološki parametri, akvatična toksičnosti i afinitet vezivanja za estrogene receptore. Izračunate su vrednosti afiniteta za 4 vrste receptora (G-protein spregnuti receptori, jonski kanali, inhibitori kinaza, nuklearni receptori). Antiproliferativna aktivnost ispitivanih derivata sukcinimida određena je primenom kolorimetrijskog testa sa tetrazolijum solima (MTT testa) na komercijalnim kulturama ćelija (MRC-5, A549, HeLa, MDA-MB-231, MCF-7, HT-29) i izračunate su IC50 vrednosti. Urađena je i doking analiza sukcinimida prema ERA (estrogen receptor alfa) i ERB (estrogen receptor beta) i dobijene su vrednosti energije formiranja kompleksa sa posmatranim receptorima (MolDock Score). Statistički najznačajnije linearne korelacije dobijene su između eksperimentalno određenih hromatografskih parametara (RM0 i S) i in silico parametara lipofilnosti MlogP i ClogP. Ispitivanjem uticaja promene RM0 i S na farmakokinetske karakteristike dobijeni su rezultati koji pokazuju paraboličnu zavisnost konstante apsorpcije (Ka) i procenta vezivanja za proteine plazme (PPB) od posmatranih retencionih konstanti, dok je zavisnost sa volumenom distribucije (Vd) i sposobnošću prolaska kroz krvno-moždanu barijeru (logBBB) bila linearnog tipa. Toksičnost ispitivanih jedinjenja, procenjena na osnovu in silico dobijenih LD50 vrednosti, nije bila viša od toksičnosti već registrovanih lekova sa strukturom sukcinimida, i dala je parabolične zavisnosti u odnosu na RM0 i S vrednosti. Eksperimentalno nijedno od ispitivanih jedinjenja nije pokazalo aktivnost u odnosu na zdrave fibroblaste pluća. Najznačajniju antiproliferativnu aktivnost (najniže IC50) su pokazala jedinjenja 6 i 7 u odnosu na ćelije linije MCF-7 i jedinjenje 11 u odnosu na A549 ćelijsku liniju. Doking analiza je pokazala niže energije formiranja kompleksa sa ERA, u odnosu na ERB. Eksperimentalno određeni parametri RM0 i S se mogu koristiti kao alternativne i pouzdane mere lipofilnosti analiziranih sukcinimida. Ispitivana jedinjenja pokazuju povoljne fizičko-hemijske karakteristike, predviđene in silico metodama i povoljne farmakokinetske karakteristike: male vrednosti konstante apsorpcije, umeren volumen distribucije, povoljan afinitet vezivanja za proteine plazme, favorizovan prolazak kroz krvno-moždanu barijeru za lipofilnija jedinjenja. Procenjuje se da sva ispitivana jedinjenja, izuzev derivata sa –CN supstituentom, imaju zahtevani nizak stepen toksičnosti. Po antiproliferativnoj aktivnosti u odnosu na ćelije ER-zavisnog karcinoma dojke (MCF-7) izdvajaju se jedinjenja sa metil i nitro supstituentom u para položaju. Na osnovu malih energija formiranja kompleksa sa ERA, koji su eksprimirani na ćelijama MCF-7 linije, pretpostavlja se da bi mehanizam njihovog delovanja delimično mogao biti objašnjen uticajem na ERA, ali su potrebna dodatna istraživanja na tom polju.
Succinimides have exhibited various pharmaceutical effects including antiproliferative activity due to an important structural fragment (a pharmacophore) presented in form of two hydrophobic regions and two electron-rich centers. Current development of new drugs involves modifications in structure (type, position and orientation of substituents) and usage of in silico computational programs to predict and optimize pharmacokinetic and safety profile of drug candidates. In early phase of drug development, databases regarding the molecular, pharmacokinetic and toxicological parameters of already tested compounds are used, mathematical models and algorithms are applied for predicting the properties of new molecules and inadequate candidates are eliminated saving time and resources. Determination of physico-chemical properties of the analyzed methyl-ethyl-N-phenilsuccinimide derivatives by software packages; virtual pharmacokinetic and toxicology screening; investigation of retention behavior of the compounds by the reversed-phase HPTLC analysis and calculation of retention constants and their correlation with lipophilicity; in vitro evaluation of antiproliferative activity toward five carcinoma cell lines and normal fetal lung cell line; molecular behavior study on target estrogen receptors by molecular docking and correlation of antiproliferative activity toward ER+ breast carcinoma cell lines and in silico estrogen receptor affinity binding. Retention behavior of 11 newly synthesized succinimide derivatives was determined by reversed phase high performance thin layer chromatography (RP HPTLC) with the application of two-component mixtures water - organic solvent (methanol, acetonitrile or acetone) with adequate volume fractions of the organic modifier. After chromatographic development RM0 and S parameters were calculated. The logarithm of partition coefficient, logP for the analyzed compounds were calculated by different softwares. Physico-chemical properties, pharmacokinetic and toxicological parameters, aquatic toxicity and relative affinity to estrogen receptors were predicted in silico. The affinity toward 4 types of receptors (G-proteine coupled receptors, ion channels, kinase inhibitors, nuclear receptors) were calculated as well. Standard MTT assay was applied to evaluate cytotoxic activities of the analyzed succinimides after cells were exposed. Antiproliferative activity were investigated toward commercial MRC-5, A549, HeLa, MDA-MB-231, MCF-7, HT-29 cell lines and IC50 values were calculated for each compound. MolDock Score that represents energy of binding to estrogen alfa and estrogen beta receptors was determined by molecular docking. Statistically significant linear correlations were determined between the chromatographic retention constants (RM0 and S) and calculated logP, and the best two were obtained in correlation of retention constants with MlogP and ClogP. The examination of RM0 and S influence on pharmacokinetics indicated parabolic dependence of the absorption constant (Ka) and plasma protein binding predictor (PPB) from the observed constants while the volume of distribution (Vd) and the ability to cross the brain blood barrier (logBBB) had linear association with the retention parameters. The toxicity of the analysed compounds evaluated in silico as LD50 on rodents was lower in comparison with the drugs with succinimide structure that are on the market and had parabolic correlation with the RM0 and S values. The experiments indicated that none of the compounds examined had cytotoxic activity toward the healthy lung fibroblast cells. The results of the in vitro assay shown that none of the investigated compounds demonstrated antiproliferative activity toward fetal lung cells. The most potent antiproliferative agents were compounds 6 and 7 toward MCF-7 cell line, and compound 11 toward A549 cell line. Molecular docking shown lower energy for binding to ERA in comparison to ERB.

Orientadores: Ricardo Aparicio, Munir Salomão Skaf
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química
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Resumo: O câncer é uma doença cuja incidência e prevalência atinge proporções alarmantes, estabelecendo-se, hoje, como um problema mundial de saúde pública. A fosforilação de proteínas é um evento dinâmico e reversível, governado pela atividade oposta de proteínas tirosina quinases e proteínas tirosina fosfatases. Níveis elevados das fosfatases LMW-PTP e CDC25B foram observados em uma ampla variedade de tumores e, assim, estas foram selecionadas como alvo para o desenvolvimento de novos inibidores. Utilizando métodos in silico, uma coleção, contendo aproximadamente 500 mil fragmentos, foi montada a partir de um banco de compostos comerciais. Para cada enzima, esses fragmentos foram submetidos a distintos protocolos de docagem molecular, através dos quais 19 pequenas moléculas foram selecionadas e adquiridas comercialmente. Os resultados computacionais foram validados por ensaios de inibição enzimática, tendo sido identificados novos esqueletos moleculares capazes de inibir mais do que 50% da atividade enzimática, obtendo-se valores de eficiência do ligante de até 0,33 kcal mol-1 por átomo diferente de hidrogênio. Paralelamente, uma série de compostos derivados do ácido benzenofosfônico foi ensaiada frente à LMW-PTP após estudos de docagem, seguindo-se estudos cristalográficos que levaram à obtenção de duas estruturas inéditas: uma com a proteína na forma apo e outra de um complexo LMW-PTP:inibidor. Além do sítio ativo já conhecido, observou-se um segundo sítio cristalográfico cuja potencial função biológica, se confirmada, poderia abrir novas possibilidades para modular a atividade da LMW-PTP, perspectiva que demanda investigação
Abstract: Cancer is a disease whose incidence and prevalence have reached alarming proportions, emerging today as a major public health problem. Protein phosphorylation is a dynamic and reversible event, governed by the opposite activities of protein tyrosine kinases and protein tyrosine phosphatases. High levels of the phosphatases LMW-PTP and CDC25B have been observed in a wide variety of tumors and, for this reason, they have been selected as targets for inhibitor development. Using in silico methods, a collection of approximately 500,000 fragments was assembled from a database of commercial compounds. For each enzyme, these fragments were subjected to different molecular docking protocols, through which 19 small molecules have been selected and purchased. The computational results were validated by enzyme inhibition assays, with the identification of new molecular scaffolds capable of inhibiting in more than 50% the enzyme activity, resulting in ligand efficiency values up to 0.33 kcal mol-1 per non-H atom. Similarly, a number of compounds derived from benzenophosphonic acid was tested against the LMW-PTP after docking studies, followed by crystallographic studies which resulted in two new structures: one of the apo protein and another of a complex LMW-PTP:inhibitor. In addition to the previously described active site, a second crystallographic site was identified, whose potential biological function, if confirmed, might open new possibilities to modulate LMW-PTP activity, in a perspective which demands further investigation.
Doutorado
Físico-Química
Doutora em Ciências

Avec plus d’un million et demi de morts chaque année, la tuberculose reste aujourd’hui la seconde cause de mortalité liée à un agent infectieux. De plus l’organisation mondiale de la santé (OMS) a estimé en 2011 qu’un tiers de la population mondiale était porteuse du bacille Mycobacterium tuberculosis responsable de la maladie. Depuis la fin des années 1980, une recrudescence du nombre de cas de tuberculose est observée à l’échelle mondiale. Cette recrudescence est due à la fois à l’apparition de souches résistantes, mais également à l’épidémie de VIH qui est un facteur de prédisposition au déclenchement de la maladie.En 2000, le répresseur transcriptionnel mycobactérien EthR a été identifié comme étant un régulateur clé dans la bioactivation de l’éthionamide (ETH), un antituberculeux utilisé pour le traitement de seconde intention. En 2009, l’inhibition de ce répresseur par le développement de molécules « drug-like » a permis de potentialiser l’activité de l’éthionamide d’un facteur 3 chez la souris infectée et a permis de valider cette cible pour une future approche thérapeutique.Ce travail repose sur la découverte et l’optimisation de nouveaux inhibiteurs de ce répresseur transcriptionnel mycobactérien, à partir d’une petite molécule appelée « fragment » qui a été cocristallisée avec la protéine. Par la combinaison d’un criblage in silico, d’un criblage in vitro des touches identifiées, de l’étude des structures radiocristallographiques des complexes ligands/protéines et de la chimie médicinale, le développement de trois approches complémentaires dites « fragmentgrowing », « fragment-merging » et « fragment-linking » a permis de développer des composés présentant de fortes activités. Ces résultats permettront très prochainement de sélectionner une nouvelle molécule issue de ce travail dans la perspective de nouveaux essais sur le modèle murin
Tuberculosis (TB) remains the leading cause of death due to a single infective agent with more than 1.5 million people killed each year. In 2011, the world health organization (WHO) estimated that one third of the world’s population is infected with Mycobacterium tuberculosis, the pathogen responsible for the disease. This phenomenon may be due to an explosive escalation of TB incidence that occurred in the 1980s due to the emergence of both resistant strains and HIV epidemic.In 2000, EthR, a mycobacterial transcriptional repressor, was identified as a key modulator of ethionamide (ETH) bioactivation. ETH is one of the main second-line drugs used to treat drug resistant strains. In 2009, it was shown that co-administration of ETH and drug-like inhibitors of EthR was able to boost ETH activity threefold in a mouse-model of TB-infection, thus validating the target for a new therapeutic strategy.This work deals with the discovery and optimisation of new EthR inhibitors, based on a small molecule, called a “fragment”, co-crystallized with the protein. We combined in silico screening, in vitro evaluation of the hit compounds, study of co-crystal structures and medicinal chemistry to develop three complementary approaches called “fragment growing”, “fragment merging” and “fragment linking” that led to the discovery of very potent inhibitors. Based on these results, we are currently selecting a potential candidate for new in vivo experiments

Malaria is a major public health problem that affects millions of lives globally. The increased burden of malaria requires new interventions that will address the eradication of the disease. Current interventions include vector control by using insecticide-treated bed nets and indoor residual spraying, and antimalarial drugs to control the parasite. Parasite resistance has been reported for the currently used effective antimalarial drugs. To pre-empt the impact of parasite resistance a continued development of new antimalarial drugs that have novel mechanisms of action should be pursued. Antimalarial drug discovery requires that potential antimalarial drugs should have different drug targets to those already targeted, to lower the chances of resistance. Potential antimalarial drugs should preferably provide a single radical cure to prevent reproduction at all life cycle stages. This study tested the effects of in silico designed compounds targeting plasmodial Ca2+- dependent protein kinases (CDPK) 1 & 4, FIKK kinases and bromodomain proteins on the Plasmodium parasite. These enzymes are involved in gene regulation and are important factors during gene transcription. In P. falciparum the gatekeeper kinases contain small hydrophobic pockets near the ATP-binding site. These hydrophobic pockets allow for selective inhibition of these proteins at the ATP-binding site. The compounds were tested in vitro to determine their antiplasmodial activity. These compounds are shown to be potential inhibitors of the intra-erythrocytic P. falciparum parasites as three of the compounds showed selective cytotoxic activity at less than 1 μM against the chloroquine sensitive laboratory strains (3D7 and NF54). Even though the proteins targeted by these compounds have been previously indicated to play a role at specific stages during the parasite’s life cycle, the compounds tested here were not able to target the sexual gametocyte stages of the Plasmodium parasite. Further optimisation of these compounds should be performed to improve activity against both the asexual and sexual stages of the parasites.
Dissertation (MSc)--University of Pretoria, 2017.
Pharmacology
MSc
Unrestricted

La medicina personalitzada i les teràpies dirigides són, avui dia, estratègies emergents en les companyies farmacèutiques. L’objectiu global, a llarg termini, és desenvolupar tractaments dirigits cap a mecanismes moleculars desregulats únicament en les cèl•lules afectades, reduint així els problemes de toxicitat d’aquests compostos. Aquest procés és llarg i costós però la introducció de les tècniques de disseny racional de fàrmacs ha permès reduir de manera considerable el temps d’identificació de molècules actives, agilitzant així les etapes inicials. Les teràpies antitumorals dirigides a promoure l’apoptosi i/o a controlar el procés de proliferació cel•lular es troben avui dia en ple desenvolupament. A més, les oportunitats d’intervenció terapèutiques en aquesta línia s’incrementen a mesura que augmenta el coneixement de les proteïnes involucrades en aquests processos. Avui dia els principals problemes dels compostos identificats radiquen però en la seva selectivitat i el gran nombre d’efectes secundaris que presenten, pel que el disseny del molècules selectives és un camp de recerca molt actiu. El present projecte es basa en la cerca de nous fàrmacs anticancerígens mitjançant la modelització molecular. D’una banda es tracta d’identificar inhibidors per a les proteïnes de la família Bcl-2 per a restablir els nivells normals d’apoptosi i, de l’altra, per a les proteïnes CDK4 i CDK6, importants reguladores del cicle cel•lular. L’objectiu plantejat a llarg termini en aquesta tesi és identificar compostos actius amb potència i selectivitat cap a aquestes proteïnes per tal de convertir-los en caps de sèrie que finalment puguin arribar a ser fàrmacs comercials. La utilització de compostos mimètics del domini BH3 per inhibir la funció dels membres antiapoptòtics de la família Bcl-2 és una de les estratègies més emprades per al control de l’apoptosi. En aquest marc, en funció de la selectivitat que presenten envers els pèptids BH3, podem trobar dues subfamílies de proteïnes antiapoptòtiques: Bcl-2, Bcl-xL i Bcl-w d’una banda i Mcl-1 i A-1 de l’altra. Diferents estudis suggereixen que per a produir la mort cel•lular és necessari intervenir al menys un membre de cadascuna de les subfamílies. Per tant, sota aquesta premissa, es van analitzar les interaccions establertes entre les proteïnes antiapoptòtiques i dominis BH3 tant pel cas de pèptids que s’uneixen amb igual afinitat a tota la família, com per a pèptids selectius de cadascun dels subgrups. Nombrosos estudis apunten a que la helicitat en els pèptids mimètics dels domini BH3 incrementa notablement l’afinitat d’enllaç. Sota aquesta premissa s’ha tractat de dissenyar pèptids derivats de la proteïna proapoptòtica Bak substituint alguns dels residus prescindibles per l’aminoàcid no natural Aib, inductor de conformacions helicoïdals. Actualment tots els inhibidors coneguts per a les CDKs, actuen sobre el lloc d’unió de l’ATP. Donat que existeix una gran quantitat de dades experimentals sobre aquests compostos es va decidir avaluar diferents algoritmes de docking i predicció d’afinitats experimentals amb cinc inhibidors coneguts de CDK6. Finalment, s’ha proposat també un desenvolupament metodològic que enfoca el problema del disseny de fàrmacs des d’una perspectiva més amplia: la quimiogenòmica. Amb la seqüenciació del genoma humà s’ha pres consciència de que resulta inviable avaluar el gran número de compostos químics coneguts actualment sobre totes les possibles dianes terapèutiques identificades en el genoma humà. Per aquest motiu és imprescindible desenvolupar mètodes teòrics més senzills per a la caracterització i comparació de molècules que permetin predir la seva activitat biològica. Així doncs, amb la realització d’aquesta tesi, queda patent que l’aplicació de mètodes teòrics pot contribuir de manera eficient al disseny de fàrmacs. D’aquesta manera es possible reduir el cost i temps necessari per al descobriment de compostos actius.
Nowadays, personalized medicine and directed therapies have emerged as appealing strategies for pharmaceutical companies. The long-term goal is developing new treatments to target molecular pathways altered only in affected cells, thus reducing undesired side effects and toxicity problems. This is a tedious and long process although the incorporation in its framework of rational drug design techniques has reduced the time needed to identify new active molecules. The knowledge of molecular mechanisms involved in a given pathology allows finding a point of the process that can be targeted, usually a protein, restoring the normal cell behavior. Once identified the therapeutic target it is possible to find compounds that reproduce interactions between this protein and the corresponding natural regulations by means of molecular modeling techniques. In principle, these compounds are expected to mimic the biological effect of the natural regulators. Antitumoral therapies oriented to promote apopotosis or control the cell proliferation process are gaining importance nowadays. In addition, opportunities for therapeutic intervention in this context are growing with the discovery of new proteins involved in these pathways. In fact, the drawback of compounds known at date relies on selectivity problems and, thus, the huge number of undesired side effects of these treatments. Hence, development of selective treatments is a very active research field. The goal of the present PhD project is to identify new anticancer agents using molecular modeling techniques. On the one hand, it has been tried to identify inhibitors of the Bcl-2 protein family in order to restore normal apoptosis levels in tumoral cells and, on the other hand, for the CDK4 and CDK6 proteins, key regulators of eukaryotic cell cycle. All these proteins are deregulated in many types of cancer and thus, are presented as interesting targets for the cancer treatment. The identification of compounds with potency and selectivity for these proteins that can be used as lead compounds that finally will become commercial drugs is seeked.

This thesis presents the application of advanced molecular dynamics techniques as "tool" in design of small molecules that bind to protein targets. In the first part, our initial goal was to understand the factors governing the molecular recognition of FKBP12 binding domain, through the study of the conformational space of known ligands with disparate affinity costants. In the second part of this thesis, results of the former part, were applied to in silico design of new high-affinity ligands. Subsequent synthesis and characterization confirm that all novel ligands have affinity in the nano molar range. Moreover, among these ligands, the compound Elte378 is, for our knowledge, the most potent synthetic inhibitor of FKBP12 to date.

Whole genome sequence of the human pathogen Chlamydophila pneumoniae and four other strains of same species were analyzed to identify drug targets. Total number 4388 protein coding genes were studied from four strains; in which 3948 genes were having more than 100 amino acids in their coding sequence were selected; we found 147 genes were identified as non-human homologs and conserved proteins among four strains. These non-human homologs genes and their encoding protein were categorized on the basis of the pathways involved in the basic survival mechanisms of the bacterium. Further, MSA of these genes showed eight different types of proteins as a novel drug target to design a drug. The modeled Holliday junction DNA helicase RuvB protein has more appropriate active sites among all other target proteins. Though all chosen drugs bind to Holliday junction DNA helicase RuvB protein, the binding site on the target protein with the minimum binding energy was selected. By using the active site prediction tools, under the optimized conditions we designed a set of antibiotics. Docking was done with the Autodock 4.0 with the different conformations of each ligand. This is the better drug that binds to the active site of target protein and inhibits their activities, which will effects one of the most essential pathways involved in DNA replication, recombination, modification and repair. Therefore, this in silico analysis provides rapid and potential approach for identification of drug target and designing of drug

Diabetes is a worldwide health issue that has been expanding mainly in developed countries. It is characterized by abnormal levels of blood sugar due to several factors. The most common are resistance to insulin and the production of defective insulin which exerts little or no effect. Its most common symptoms include tissue damage to several systems due to elevated levels of blood sugar. One of the key enzymes in hydrocarbon metabolism is α-glucosidase (EC 3.2.1.20). It catalyzes the breakdown of complex carbohydrates into their respective monomers (glucose) which allows them to be absorbed. In this work, caffeoyl quinic acids and their metabolites were analyzed as potential inhibitors for α-glucosidase. The search for the best inhibitor was conducted using molecular docking. The affinity of each compound was compared to the inhibitor present in the crystal structure of the protein. As no inhibitor with a similar affinity was´found, a new approach was used, in situ drug design. It was not possible to achieve an inhibitor capable of competing with the one present in the crystal structure of the enzyme, which is also its current commercial inhibitor. It is possible to draw some conclusions as to which functional groups interact best with certain residues of the active site. This work was divided into three main sections. The first section, Diabetes, serves as an introduction to what is Diabetes, its symptoms and/or side effects and how caffeoyl quinic acids could be used as a treatment. The second section, Caffeoylquinic acids and their metabolites as inhibitors for Alfa-glucosidase, corresponds to the search through molecular docking of caffeoyl quinic acids as inhibitors for α-glucosidase and what was possible to draw from this search. The last section, In situ design of an inhibitor for α-glucosidase (EC 3.2.1.20), corresponds to the in situ drug design study and what it achieved. The representation of each of the molecules used as a ligand can be found in the Annexes.
Universidade da Madeira

Εξήντα έξη χρόνια μετά την εμφάνιση της πρώτης δημοσίευσης που αφορούσε στη θεραπεία με τη χρήση μουσταρδών αζώτου και ενώσεις που ανήκουν στη θεραπευτική αυτή κατηγορία, όπως το κυκλοφωσφαμίδιο και η μελφαλάνη εξακολουθούν να αποτελούν πρώτης γραμμής χημειοθεραπευτικούς παράγοντες τόσο κατά της λευχαιμίας όσο και έναντι άλλων συμπαγών όγκων. Οι διλειτουργικοί αλκυλιωτικοί παράγοντες, κατηγορία στην οποία ανήκουν και οι μουστάρδες αζώτου, επάγουν το θάνατο των καρκινικών κυττάρων και κατά συνέπεια και την κυτταροτοξική τους δράση μέσω της δημιουργίας διαμοριακών χιαστί τύπου δεσμών μεταξύ των κλώνων του DNA. Οι φαρμακολογικές τους δράσεις σχετίζονται κυρίως με την σύνθεση του DNA των διαιρούμενων κυττάρων, προκαλώντας ουσιαστικά μια γενική αναστολή της κυτταρικής διαίρεσης. Ωστόσο, εκτός από την αναμενόμενη και επιθυμητή θεραπευτική δράση, προκαλούν τοξικές παρενέργειες, οι οποίες σχετίζονται με μεταλλαγή των κυττάρων της αρχέγονης σειράς, εμφάνιση καρκινογένεσης και τερατογένεσης. Το εύρος των μειονεκτημάτων που παρουσιάζουν και ειδικά η συστηματική τοξικότητα σε συνδυασμό με την υψηλή χημική in vivo δραστικότητα τους και την μειωμένη εκλεκτικότητα τους, είχαν ως αποτέλεσμα τον περιορισμό της χρήσης τους. Παρόλα αυτά κατέχουν εξέχουσα θέση στη θεραπευτική έναντι μιας μεγάλης ποικιλίας τύπων καρκίνου, συμπεριλαμβανομένου και των αιματολογικών νεοπλασμάτων. Στην προσπάθεια επίλυσης του προβλήματος της αυξημένης τοξικότητας και της απουσίας εκλεκτικότητας των ενώσεων της κατηγορίας αυτής, διάφορες μουστάρδες αζώτου συζεύχθηκαν μέσω εστερικού δεσμού με ποικίλους στεροειδικούς σκελετούς, στρατηγική που αποδείχθηκε ουσιαστικά ιδιαιτέρως αποτελεσματική. Αποτελέσματα μελετών τόσο της ερευνητικής μας ομάδας όσο και άλλων, υποστηρίζουν πως ο στεροειδικός σκελετός δεν μπορεί πλέον να θεωρηθεί μόνο ως απλός φορέας για την αποτελεσματική μεταφορά της αλκυλιωτικής ομάδας στις θέσεις στόχους του DNA, εφόσον μικρές δομικές τροποποιήσεις του επιφέρουν σημαντικές διαφοροποιήσεις στην αντιλευχαιμική δράση των τελικών στεροειδών εστέρων. Επιπρόσθετα, οι μελέτες αυτές έδειξαν ότι η παρουσία της –NHCO- ομάδας είτε ως ενδοκυκλικής λακταμικής είτε ως εξωκυκλικής αμιδικής στον Δ-δακτύλιο του στεροειδικού τμήματος είναι καθοριστικός παράγοντας για την εμφάνιση κυτταροτοξικής ή αντινεοπλασματικής δράσης στεροειδών εστέρων της χλωραμβουκίλης και αναλόγων αυτής. Μέχρι σήμερα έχει προκύψει ένας εκτεταμένος αριθμός στεροειδών εστέρων, από την σύζευξη απλών και τροποποιημένων στεροειδών με αρκετές διαφορετικές μουστάρδες αζώτου. Η πλειονότητα αυτών των παραγώγων έχουν υποβληθεί σε in vitro και in vivo βιολογικές δοκιμές έναντι των λευχαιμίων Ρ388 και L1210 και αρκετά από αυτά έχουν αποδειχθεί αποτελεσματικοί αντινεοπλασματικοί παράγοντες. Σε μια πρόσφατη 3D-QSAR μελέτη τριάντα οκτώ στεροειδών εστέρων τριών διαφορετικών μουσταρδών αζώτου με απλούς και τροποποιημένους στεροειδικούς σκελετούς, έγινε προσπάθεια διερεύνησης των 3D σχέσεων χημικής δομής-βιολογικής δραστικότητας, με σκοπό την εύρεση των απαραίτητων στερεοηλεκτρονικών χαρακτηριστικών των ενώσεων που συμβάλλουν στην εκδήλωση της αντιλευχαιμικής δράσης των. Η ανάλυση στηρίχθηκε στην χρήση των μεθοδολογιών CoMSIA και CoMFA. Τα δεδομένα που ελήφθησαν από τις 3D-QSAR αναλύσεις αξιοποιήθηκαν στη συνέχεια από ένα υπολογιστικό πρόγραμμα de novo σχεδιασμού και ανακάλυψης νέων βιοδραστικών μορίων, την εφαρμογή LeapFrog. Με βάση τα είκοσι βελτιωμένα στεροειδικά εστερικά παράγωγα που προτάθηκαν από το LeapFrog, επιλέχθηκαν να σχεδιαστούν και να συντεθούν οι ακόλουθες αρωματικές μουστάρδες αζώτου: α) 2-[π-Ν,Ν-δις(2-χλωροαιθυλ)αμινοφαινυλο]βουτυρικό οξύ (7), β) 2-ακεταμιδο-2-[π-Ν,Ν-δις(2-χλωροαιθυλ)αμινοφαινυλο]οξικό οξύ (30), γ) 2-ακεταμιδο-2-[ο-Ν,Ν-δις(2-χλωροαιθυλ)αμινοφαινυλο]οξικό οξύ (31) και δ) το 3-ακεταμιδο-3-[π-Ν,Ν-δις(2-χλωροαιθυλ)αμινοφαινυλο] προπανοϊκό οξύ (42), καθώς και τα εστεροποιημένα παράγωγα αυτών, με επιλεγμένους απλούς και τροποποιημένους στεροειδικούς σκελετούς. Η σύζευξη των νεων μουσταρδών με επιλεγμένες στεροειδικές αλκοόλες απέδωσε δεκαεπτά νέα εστερικά ανάλογα, η σύνθεση των οποίων είχε ως απώτερο σκοπό τη βελτίωση του θεραπευτικού δείκτη των μουσταρδών αζώτου καθώς και τον εμπλουτισμό της βιβλιοθήκης των αποτελεσμάτων που αφορούν στη σχέση χημικής δομής-βιολογικής δραστικότητας των ενώσεων της κατηγορίας αυτής. Συγκεκριμένα, για τη σύνθεση των παραπάνω μουσταρδών αζώτου, εφαρμόστηκε η κλασσική μεθοδολογία σύνθεσης. Ωστόσο, αυτή αποδείχθηκε αποδοτική μονό κατά τη σύνθεση της μουστάρδας 7, παρέχοντας το τελευταίο σε συνολική απόδοση 45%. Για τις υπόλοιπες μουστάρδες ακολουθήθηκαν εναλλακτικές πορείες σύνθεσης λόγω προβλημάτων που παρουσιάστηκαν κατά την εφαρμογή της κλασσικής μεθοδολογίας. Κρίσιμο στάδιο κατά τη σύνθεση των μουσταρδών αζώτου 30 και 31, αποτέλεσε η αρχική προστασία της ελεύθερης αμινομάδας της DL-α-φαινυλγλυκίνης (16) που χρησιμοποιήθηκε ως πρώτη ύλη της συνθετικής πορείας. Η διερεύνηση και η βελτιστοποίηση των πειραματικών συνθηκών ήταν απαραίτητη και κατά το στάδιο της χλωρίωσης των Ν,Ν-δις(2-υδροξυαιθυλ)-παραγώγων 26 και 27 για τον σχηματισμό της χαρακτηριστικής Ν,Ν-δις(2-χλωροαιθυλαμινο)-ομάδας των παραγώγων 30 και 31. Κατά τη σύνθεση του 3-ακεταμιδο-3-[π-Ν,Ν-δις(2-χλωροαιθυλ)αμινοφαινυλο]προπανοϊκού οξέος (42) ήταν απαραίτητη η βελτιστοποίηση παρασκευής των ενδιαμέσων 33 και 37. Μετά από διερευνητικές προσπάθειες κατέστη εφικτή η βελτίωση της απόδοσης σύνθεσης του παραγώγου 33 από 54% σύμφωνα με τη βιβλιογραφία σε 98%, καθώς και η σύνθεση του ακετάμιδο παραγώγου 37 τόσο σε λιγότερα συνθετικά στάδια και σε καλύτερη απόδοση σε σχέση με τα δημοσιευμένα βιβλιογραφικά δεδομένα. Σε επόμενο στάδιο της μελέτης σχεδιάσθηκε η εστεροποίηση των μουστάρδων 7, 30 και 42 με επιλεγμένους στεροειδικούς σκελετούς. Για τη σύνθεση των τελικών εστερικών στεροειδικών παραγώγων εφαρμόστηκε η μέθοδος των μικτών ανυδριτών, η οποία περιλαμβάνει την αντίδραση της αρωματικής μουστάρδας αζώτου με ελαφρά περίσσεια 2,4,6-τριχλωροβενζοϋλοχλωρίδιου παρουσία τριαιθυλαμίνης, το σχηματισμό του αντίστοιχου μικτού ανυδρίτη και στη συνέχεια in situ αντίδρασή του με τη στεροειδική αλκοόλη παρουσία 4-διμεθυλαμινοπυριδίνης. Τελικώς κατέστη εφικτή η σύνθεση δεκαεπτά τελικών στεροειδών εστέρων από τη σύζευξη των μουσταρδών αζώτου, 7 και 42 με επιλεγμένες στεροειδείς αλκοόλες. Παρά τις διερευνητικές προσπάθειες που καταβλήθησαν δεν κατέστη εφικτή η εστεροποίηση της μουστάρδας 30. Το σύνολο των τελικών στεροειδών εστέρων προωθήθηκαν σε βιολογικές μελέτες για την αποτίμηση της αντινεοπλασματικής τους δράσης. Τα διαθέσιμα αποτελέσματα αυτών των μελετών σχετίζονται με τα έντεκα στεροειδικά εστερικά παράγωγα της μουστάρδας 7 (2-PHE-BU). Τα μελετηθέντα αυτά παράγωγα επέδειξαν μειωμένη τοξικότητα και μια οριακή αντινεοπλασματική δραστικότητα έναντι της λευχαιμίας Ρ388, στην οποία είχαν μελετηθεί, συγκριτικά με την ελέυθερη αρωματική μουστάρδα (2-PHE-Bu). Ωστόσο, τα ληφθέντα βιολογικά αποτελέσματα ήταν υποδεέστερα των αντίστοιχων δεδομένων που είχαν συλλεχθεί κατά τη μελέτη του PHE και των στεροειδικών εστέρων αυτού έναντι και πάλι της λευχαιμίας Ρ388. Το γεγονός αυτό πιθανόν να οφείλεται στη μειωμένη ενζυμική υδρόλυση που υφίστανται in vivo τα παράγωγα αυτά, λόγω της στερεοχημικής παρεμπόδισης που προκαλεί η αιθυλική αλυσίδα γύρω από τον εστερικό δεσμό σύνδεσης μουστάρδας-στεροειδούς, γεγονός που συνεπάγεται μειωμένη απελευθέρωση της μουστάρδας αζώτου. Στο σημείο αυτό αξίζει να αναφερθεί πως αν και, τόσο οι νέες αρωματικές μουστάρδες αζώτου, όσο και τα στεροειδικά τους παράγωγα είχαν προταθεί ως υποψήφια παράγωγα με βελτιωμένη βιοδραστικότητα κατά την πραγματοποίηση de novo σχεδιασμού από το υπολογιστικό πρόγραμμα LeapFrog, τα αποτελέσματα των βιολογικών δοκιμών δεν επιβεβαιώσαν τις συγκεκριμένες ποτάσεις. Πιθανότατα, παράμετροι που δεν ελήφθησαν υπόψη κατά τον de novo σχεδιασμό από το LeapFrog, όπως η μεταβολική τροποποίηση των ενώσεων να εμπλέκονται και να καθορίζουν την βιοδραστικότητα του τελικών στεροειδικών εστέρων. Θεωρείται ότι μια αναθεώρηση κρίσιμων παραμέτρων όπως η χημική ποικιλομορφία και ο αριθμός των ενώσεων που εισέρχονται ως δεδομένα στις μελέτες 3D-QSAR μπορεί να αποδώσει μεγαλύτερης αξιοπίστιας μοντέλα CoMFA και CoMSIA. Τα νέα αυτά μοντέλα κατά την εισαγωγή τους σε υπολογιαστικά προγράμματα de novo σχεδιασμού μπορούν να συμβάλλουν στο σχεδιασμό νεών ενώσεων με πιθανά υπέρτερη βιοδραστικότητα.
Sixty-six years after the serendipitous discovery and the first publication referred to nitrogen mustard therapy, nitrogen mustards such as cyclophosphamide and melphalan are still front-line chemotherapeutic agents for the treatment of leukemia and various solid tumors. Several chemotherapeutics act as DNA-damaging agents resulting in cell cycle arrest and cell death of the uncontrollably proliferating cancer cells. Among them, bifunctional DNA alkylating agents, such as the nitrogen mustards, form intrestrand crosslinks (ICLs), extremely cytotoxic lesions, blocking DNA replication and transcription. However, cellular responses triggered by ICLs can cause resistance in tumor cells, limiting the efficacy of such treatment. Cytotoxicity, mutagenesis, and clastogenesis are attributed to their ability to damage DNA. Although, these drugs remain some of the most commonly prescribed chemotherapies for the treatment of various solid and hematological malignancies, particularly in combination with other classical or target therapeutics in multi-agent regimens, severe side effects on normal tissues comprise drawbacks of their use. These are attributed to their low selectivity to alkylate specific DNA bases due to their high inherent reactivity, resulting in the non-specific alkylation of other cellular nucleophilic species such as amino acid residues or low molecular weight thiols. Several approaches have been explored to reduce the toxicity and increase the therapeutic efficacy of nitrogen mustards. Among them, the generation of DNA-directed alkylating agents via the chemical linkage of nitrogen mustards with molecules of increased DNA-binding affinity and the synthesis of nitrogen mustard prodrugs led to interesting results. The chemical linkage of nitrogen mustards to carrier molecules (e.g steroids) with affinity for specific binding sites (nuclear receptors) has been used aiming at the improvement of the antineoplastic treatment. Our ongoing studies in this field have demonstrated that steroidal esteric derivatives of aromatic nitrogen mustards increase the damaging effects on specific DNA sequences and achieve better selectivity and reduced toxicity compared to nitrogen mustards themselves. Steroidal skeletons, which incorporate a –NHCO- moiety are considered more appropriate modules than the common or non-modified steroids, since their esters with aromatic nitrogen mustards, such as chlorambucil and its analogs, have been proved potent antileukemic agents. To this direction, our group has published a series of studies related with steroidal esters of aromatic nitrogen mustards as antineoplastic, especially antileukemic agents. Our efforts have succeeded in the identification of potent and promising derivatives with enhanced activity and reduced toxicity compared to the corresponding nitrogen mustards against in vitro and in vivo experimental tumors. Extensive structure-activity relationship (SAR) studies have demonstrated unique structural features of both the steroidal part and the nitrogen mustard which contribute substantially to the bioactivity of the target steroidal esters Furthermore, recent 3D QSAR/CoMFA and CoMSIA studies led to the generation of related models which indicated the influence of stereoelectronic and physicochemical parameters on the antileukemic activity of target compounds. The reliability of both models was evaluated and their predictive ability on the activity of a test set of compounds proved satisfactory. Furthermore, based on the proposed CoMFA model and using the de novo ligand design routine LeapFrog of SYBYL, a series of candidate molecules with potentially optimal bioactivity was proposed, creating new challenges in further investigation of this class of compounds. Prompted by the aforementioned results and extending our structure-activity relationship studies, we decided to investigate if the incorporation of in silico predictive nitrogen mustards on various simple and modified steroids might result to steroidal esters with improved antineoplastic activity. The selection of the nitrogen mustards which were synthesized and used in this study was based on the predictive antileukemic activity of their corresponding steroidal esters and the synthetic accessibility of the intermediate and target compounds. Thus, we designed and synthesized a new series of steroidal esters containing the aromatic nitrogen mustards 2-[4-N,N-bis(2-chloroethyl)amino-phenyl]butanoic acid (2-PHE-BU, 7), 2-acetamido-2-[p-N,N-bis(2-chloroethyl)amino-phenyl]acetic acid (30), 2-acetamido-2-[o-N,N-bis(2-chloroethyl)amino-phenyl]acetic acid (31) and 3-acetamido-3-[p-N,N-bis(2-chloroethyl)amino-phenyl]propanoic acid (42). The chemical linkage of nitrogen mustards 7 and 42 with simple and modified steroids led to the synthesis of seventeen new steroidal esters aiming at the investigation of new compounds with enhanced antineoplastic activity and higher therapeutic index. The synthesis of the aforementioned nitrogen mustards was based on a classic synthetic approach. However, this procedure proved efficient only for the synthesis of compound 7, in an overall yield of 45%. Key step for the synthesis of nitrogen mustards 30 and 31 was the protection of the free amino-group of DL--phenyglycine. Optimization of the experimental conditions were also necessary for the chlorination of N,N-bis(2-hydroxyethyl) intermediates 26 and 27, which led to the corresponding nitrogen mustards 30 and 31. During the synthesis of the 3-acetamido-3-[p-N,N-bis(2-chloroethyl)amino]propanoic acid (42), optimization of the procedure for the preparation of the intermediates 33 and 37 was also necessary. Our attempts resulted in the preparation of compound 37 in less steps and higher yield (98%) compared to that referred in the literature. The synthesis of the final steroidal esteric derivatives was based on the well established method of mixed anhydrides, which involves the reaction of the aromatic nitrogen mustard with a slight excess of 2,4,6-trichlorobenzoyl chloride in the presence of triethylamine, followed by the addition of steroidal alcohol in the presence of 4-dimethylaminopyridine. The newly synthesized alkylating steroidal esters exhibited reduced toxicity and slightly improved antileukemic activity against P388 leukemia bearing mice compared to the free nitrogen mustard 2-PHE-BU. Nevertheless, they did not prove superior to already synthesized, structurally related steroidal esters of PHE indicating that the enzymatic hydrolysis and the liberation of the nitrogen mustard in vivo is possibly disfavored due to the steric hindrance of the ethyl group around the formed ester bond. Nevertheless, the biological results obtained in the present study clearly indicate that except of the important stereoelectronic requirements which are considered and incorporated as data in LeapFrog routine, other parameters are possibly implicated and determine the bioactivity of the target steroidal esters. We expect that a careful revision of the implicated parameters such as the chemical diversity and the number of the tested compounds will allows us the generation of new CoMFA and CoMSIA models which subsequently will contribute to higher predicted reliability of the in silico design by software packages such as LeapFrog.

The thesis specializes in the computational description of pharmaceutically important compounds. A substantial number of pharmaceutical drugs are small molecules that are bound to an active site of an enzyme by the "lock (binding site) and key (drug)" model through non-covalent interactions. The association of enzymes with drugs cause an increase or decrease in the activity of enzymes. The main topic is focused on the computational elucidation of the structural basis for the interactions of the purine-like compounds with the enzyme cyclin- dependent kinase 2 that belongs to the protein-kinase enzyme family. These enzymes play an important role in the cell cycle regulation; their increased activity significantly contributes to the loss of control over cell proliferation, which is one of the primary causes of cancer cell formation. The study describes the binding motifs of roscovitine, which shows an inhibitory effect on the function of cyclin-dependent kinases, and its analogues containing bioisosteric central heterocycles in the complex with cyclin-dependent kinase 2. The binding affinity between the cyclin-dependent kinase 2 enzyme and the inhibitors was quantified as calculated binding scores and evaluated in relation to the conformation of the optimized structures. The hybrid model combining the...