Synthesis, antiangiogenesis evaluation and molecular docking studies of 1-Aryl-3-[(thieno[3,2-b]pyridin-7-ylthio)phenyl]ureas: Discovery of a new substitution pattern for type II VEGFR-2 Tyr kinase inhibitors

The synthesis and biological evaluation of novel 1-aryl-3-[2-, 3- or 4-(thieno[3,2-b]pyridin-7-ylthio)phenyl]ureas 3, 4 and 5 as VEGFR-2 tyrosine kinase inhibitors, are reported. The 1-aryl-3-[3-(thieno[3,2-b]pyridin-7-ylthio)phenyl]ureas 4a-4h, with the arylurea in the meta position to the thioether, showed the lowest IC50 values in enzymatic assays (10-206 nM), the most potent compounds 4d-4h (IC50 10-28 nM) bearing hydrophobic groups (Me, F, CF3 and Cl) in the terminal phenyl ring. A convincing rationalization was achieved for the highest potent compounds 4 as type II VEGFR-2 inhibitors, based on the simultaneous presence of: (1) the thioether linker and (2) the arylurea moiety in the meta position. For compounds 4, significant inhibition of Human Umbilical Vein Endothelial Cells (HUVECs) proliferation (BrdU assay), migration (wound-healing assay) and tube formation were observed at low concentrations. These compounds have also shown to increase apoptosis using the TUNEL assay. Immunostaining for total and phosphorylated (active) VEGFR-2 was performed by Western blotting. The phosphorylation of the receptor was significantly inhibited at 1.0 and 2.5 microM for the most promising compounds. Altogether, these findings point to an antiangiogenic effect in HUVECs.

Synthesis, binding affinity, and molecular docking analysis of new benzofuranone derivative as pontential antipsychotics

The complex etiology of schizophrenia has prompted researchers to develop clozapine-related multitargetstrategies to combat its symptoms. Here we describe a series of new 6-aminomethylbenzofuranones in aneffort to find new chemical structures with balanced affinities for 5-HT2 and dopamine receptors. Throughbiological and computational studies of 5-HT2A and D2 receptors, we identified the receptor serine residuesS3.36 and S5.46 as the molecular keys to explaining the differences in affinity and selectivity betweenthese new compounds for this group of receptors. Specifically, the ability of these compounds to establishone or two H-bonds with these key residues appears to explain their difference in affinity. In addition, wedescribe compound 2 (QF1004B) as a tool to elucidate the role of 5-HT2C receptors in mediating antipsychoticeffects and metabolic adverse events. The compound 16a (QF1018B) showed moderate to high affinitiesfor D2 and 5-HT2A receptors, and a 5-HT2A/D2 ratio was predictive of an atypical antipsychotic profile.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: Molecular docking and 3D QSAR studies

The glycolytic enzyme glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) is as an attractive target for the development of novel antitrypanosomatid agents. In the present work, comparative molecular field analysis and comparative molecular similarity index analysis were conducted on a large series of selective inhibitors of trypanosomatid GAPDH. Four statistically significant models were obtained (r(2) > 0.90 and q(2) > 0.70), indicating their predictive ability for untested compounds. The models were then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results. Molecular modeling studies provided further insight into the structural basis for selective inhibition of trypanosomatid GAPDH.

A tellurium-based cathepsin B inhibitor: Molecular structure, modelling, molecular docking and biological evaluation

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Molecular Docking and Molecular Dynamic Studies of Semi-Synthetic Piperidine Alkaloids as Acetylcholinesterase Inhibitors

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Synthesis, anti-inflammatory activity and molecular docking studies of 2,5-diarylfuran amino acid derivatives

A series of 2,5-diaryl substituted furans functionalized with several amino acids were synthesized and evaluated as the cyclooxygenases COX-1 and COX-2 enzymes inhibitors. The proline-substituted compound inhibited PGE(2) secretion by LPS-stimulated neutrophils, suggesting selectivity for COX-2. Molecular docking studies in the binding site of COX-2 were performed. (C) 2011 Elsevier Masson SAS. All rights reserved.

Synthesis, biological evaluation and molecular docking studies of 3-(triazolyl)coumarin derivatives: Effect on inducible nitric oxide synthase

A series of 3-(triazolyl)-coumarins were synthesized and tested as anti-inflammatory agents. It was possible to infer that these compounds do not alter the interaction of LPS with TLR-4 or TLR-2, as the intracellular pathways involved in the TNF-alpha secretion and COX-2 activity were not affected. Nevertheless, the compounds inhibited iNOS-derived NO production, without affecting the eNOS activity. The outcome of the docking studies showed that it pi center dot center dot center dot pi interactions with the heme group are important for the iNOS inhibition, thus making compound 3c a promising lead. Moreover, the efficacy of this compound was visualized by the reduced number of neutrophils in the LPS-inflamed subcutaneous tissue. Together, biological and docking data show that triazolyl-substituted coumarins, that can act on iNOS, are a good scaffold to be explored. (C) 2012 Elsevier Masson SAS. All rights reserved.

A tellurium-based cathepsin B inhibitor: Molecular structure, modelling, molecular docking and biological evaluation

The crystallographically determined structure of biologically active 4,4-dichloro-1,3-diphenyl-4-telluraoct-2-en-1-one, 3, shows the coordination geometry for Te to be distorted psi-pentagonal bipyramidal based on a C2OCl3(lone pair) donor set. Notable is the presence of an intramolecular axial Te center dot center dot center dot O (carbonyl) interaction, a design element included to reduce hydrolysis. Raman and molecular modelling studies indicate the persistence of the Te center dot center dot center dot O(carbonyl) interaction in the solution (CHCl3) and gasphases, respectively. Docking studies of 3' (i.e. original 3 less one chloride) with Cathepsin B reveals a change in the configuration about the vinyl C = C bond. i.e. to E from Z (crystal structure). This isomerism allows the optimisation of interactions in the complex which features a covalent Te-SGCys29 bond. Crucially, the E configuration observed for 3' allows for the formation of a hypervalent Te center dot center dot center dot O interaction as well as an O center dot center dot center dot H-O hydrogen bond with the Gly27 and Glu122 residues, respectively. Additional stabilisation is afforded by a combination of interactions spanning the S1, S2, S1' and S2' sub-sites of Cathepsin B. The greater experimental inhibitory activity of 3 compared with analogues is rationalised by the additional interactions formed between 3' and the His110 and His111 residues in the occluding loop, which serve to hinder the entrance to the active site. (C) 2012 Elsevier B.V. All rights reserved.

Insect growth regulators as potential insecticides to control olive fruit fly (Bactrocera oleae Rossi): insect toxicity bioassays and molecular docking approach

Olive fruit fly, Bactrocera oleae (Rossi), is a key pest in olive orchards, causing serious economic damage. To date, the pest has already developed resistance to the insecticides commonly applied to control it. Thus, in searching for new products for an accurate resistance management programme, targeting the ecdysone receptor (EcR)might provide alternative compounds for use in such programmes. RESULTS: Residual contact and oral exposure in the laboratory of B. oleae adults to the dibenzoylhydrazine-based compounds methoxyfenozide, tebufenozide and RH-5849 showed different results. Methoxyfenozide and tebufenozide did not provoke anynegative effectsontheadults,but RH-5849 killed98-100%of the treated insects15 days after treatment. Theligand-binding domain (LBD) of the EcR of B. oleae (BoEcR-LBD) was sequenced, and a homology protein model was constructed. Owing to a restricted extent of the ligand-binding cavity of the BoEcR-LBD, docking experiments with the three tested insecticides showed a severe steric clash in the case of methoxyfenozide and tebufenozide, while this was not the case with RH-5849. CONCLUSION: IGR molecules similar to the RH-5849 molecule, and different from methoxyfenozide and tebufenozide, might have potential in controlling this pest.

Modelling the structure of latexin-carboxypeptidase A complex based on chemical cross-linking and molecular docking

We have determined the three-dimensional structure of the protein complex between latexin and carboxypeptidase A using a combination of chemical cross-linking, mass spectrometry and molecular docking. The locations of three intermolecular cross-links were identified using mass spectrometry and these constraints were used in combination with a speed-optimised docking algorithm allowing us to evaluate more than 3 x 10(11) possible conformations. While cross-links represent only limited structural constraints, the combination of only three experimental cross-links with very basic molecular docking was sufficient to determine the complex structure. The crystal structure of the complex between latexin and carboxypeptidase A4 determined recently allowed us to assess the success of this structure determination approach. Our structure was shown to be within 4 angstrom r.m.s. deviation of C alpha atoms of the crystal structure. The study demonstrates that cross-linking in combination with mass spectrometry can lead to efficient and accurate structural modelling of protein complexes.

Peptide binding prediction for the human class II MHC allele HLA-DP2:a molecular docking approach

MHC class II proteins bind oligopeptide fragments derived from proteolysis of pathogen antigens, presenting them at the cell surface for recognition by CD4+ T cells. Human MHC class II alleles are grouped into three loci: HLA-DP, HLA-DQ and HLA-DR. In contrast to HLA-DR and HLA-DQ, HLA-DP proteins have not been studied extensively, as they have been viewed as less important in immune responses than DRs and DQs. However, it is now known that HLA-DP alleles are associated with many autoimmune diseases. Quite recently, the X-ray structure of the HLA-DP2 molecule (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR a-chain has been determined. In the present study, we applied a validated molecular docking protocol to a library of 247 modelled peptide-DP2 complexes, seeking to assess the contribution made by each of the 20 naturally occurred amino acids at each of the nine binding core peptide positions and the four flanking residues (two on both sides).

EpiDOCK:a molecular docking-based tool for MHC class II binding prediction

Cellular peptide vaccines contain T-cell epitopes. The main prerequisite for a peptide to act as a T-cell epitope is that it binds to a major histocompatibility complex (MHC) protein. Peptide MHC binder identification is an extremely costly experimental challenge since human MHCs, named human leukocyte antigen, are highly polymorphic and polygenic. Here we present EpiDOCK, the first structure-based server for MHC class II binding prediction. EpiDOCK predicts binding to the 23 most frequent human, MHC class II proteins. It identifies 90% of true binders and 76% of true non-binders, with an overall accuracy of 83%. EpiDOCK is freely accessible at http://epidock.ddg-pharmfac. net. © The Author 2013. Published by Oxford University Press. All rights reserved.

Histidine hydrogen bonding in MHC at pH 5 and pH 7 modeled by molecular docking and molecular dynamics simulations

Hydrogen bonds play important roles in maintaining the structure of proteins and in the formation of most biomolecular protein-ligand complexes. All amino acids can act as hydrogen bond donors and acceptors. Among amino acids, Histidine is unique, as it can exist in neutral or positively charged forms within the physiological pH range of 5.0 to 7.0. Histidine can thus interact with other aromatic residues as well as forming hydrogen bonds with polar and charged residues. The ability of His to exchange a proton lies at the heart of many important functional biomolecular interactions, including immunological ones. By using molecular docking and molecular dynamics simulation, we examine the influence of His protonation/deprotonation on peptide binding affinity to MHC class II proteins from locus HLA-DP. Peptide-MHC interaction underlies the adaptive cellular immune response, upon which the next generation of commercially-important vaccines will depend. Consistent with experiment, we find that peptides containing protonated His residues bind better to HLA-DP proteins than those with unprotonated His. Enhanced binding at pH 5.0 is due, in part, to additional hydrogen bonds formed between peptide His+ and DP proteins. In acidic endosomes, protein His79β is predominantly protonated. As a result, the peptide binding cleft narrows in the vicinity of His79β, which stabilizes the peptide - HLA-DP protein complex. © 2014 Bentham Science Publishers.

Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0:a quantitative molecular docking study

Background: HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 - 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pKa of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0. Results: The X-ray structure of the peptide - HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides. Conclusions: The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ε-nitrogen of His 79β. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins. © 2012 Patronov et al.; licensee BioMed Central Ltd.