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.

Docking and molecular dynamics simulation of quinone compounds with trypanocidal activity

In this work, two different docking programs were used, AutoDock and FlexX, which use different types of scoring functions and searching methods. The docking poses of all quinone compounds studied stayed in the same region in the trypanothione reductase. This region is a hydrophobic pocket near to Phe396, Pro398 and Leu399 amino acid residues. The compounds studied displays a higher affinity in trypanothione reductase (TR) than glutathione reductase (GR), since only two out of 28 quinone compounds presented more favorable docking energy in the site of human enzyme. The interaction of quinone compounds with the TR enzyme is in agreement with other studies, which showed different binding sites from the ones formed by cysteines 52 and 58. To verify the results obtained by docking, we carried out a molecular dynamics simulation with the compounds that presented the highest and lowest docking energies. The results showed that the root mean square deviation (RMSD) between the initial and final pose were very small. In addition, the hydrogen bond pattern was conserved along the simulation. In the parasite enzyme, the amino acid residues Leu399, Met400 and Lys402 are replaced in the human enzyme by Met406, Tyr407 and Ala409, respectively. In view of the fact that Leu399 is an amino acid of the Z site, this difference could be explored to design selective inhibitors of TR.

Novel aryl beta-aminocarbonyl derivatives as inhibitors of Trypanosoma cruzi trypanothione reductase: binding mode revised by docking and GRIND2-based 3D-QSAR procedures

Trypanothione reductase has long been investigated as a promising target for chemotherapeutic intervention in Chagas disease, since it is an enzyme of a unique metabolic pathway that is exclusively present in the pathogen but not in the human host, which has the analog Glutathione reductase. In spite of the present data-set includes a small number of compounds, a combined use of flexible docking, pharmacophore perception, ligand binding site prediction, and Grid-Independent Descriptors GRIND2-based 3D-Quantitative Structure-Activity Relationships (QSAR) procedures allowed us to rationalize the different biological activities of a series of 11 aryl beta-aminocarbonyl derivatives, which are inhibitors of Trypanosoma cruzi trypanothione reductase (TcTR). Three QSAR models were built and validated using different alignments, which are based on docking with the TcTR crystal structure, pharmacophore, and molecular interaction fields. The high statistical significance of the models thus obtained assures the robustness of this second generation of GRIND descriptors here used, which were able to detect the most important residues of such enzyme for binding the aryl beta-aminocarbonyl derivatives, besides to rationalize distances among them. Finally, a revised binding mode has been proposed for our inhibitors and independently supported by the different methodologies here used, allowing further optimization of the lead compounds with such combined structure- and ligand-based approaches in the fight against the Chagas disease.

In silico screening of HIV-1 non-nucleoside reverse transcriptase and protease inhibitors

Two targets, reverse transcriptase (RT) and protease from HIV-1, were used during the past two decades to the discovery of non-nucleoside reverse transcriptase inhibitors (NNRTI) and protease inhibitors (PI) that belong to the arsenal of the antiretroviral therapy. Herein these enzymes were chosen as templates for conducting a computer-aided ligand design. Ligand and structure-based drug designs were the starting points to select compounds from a database bearing more than five million compounds by means of cheminformatic tools. New promising lead structures are retrieved from the database, which are open to acquisition and test. Classes of molecules already described as NNRTI or PI in the literature also came out and were useful to prove the reliability of the workflow, and thus validating the work carried out so far. (c) 2007 Elsevier Masson SAS. All rights reserved.

Flexibility and inhibitor binding in Cdc25 phosphatases

Cdc25 phosphatases involved in cell cycle checkpoints are now active targets for the development of anti-cancer therapies. Rational drug design would certainly benefit from detailed structural information for Cdc25s. However, only apo- or sulfate-bound crystal structures of the Cdc25 catalytic domain have been described so far. Together with previously available crystalographic data, results from molecular dynamics simulations, bioinformatic analysis, and computer-generated conformational ensembles shown here indicate that the last 30-40 residues in the C-terminus of Cdc25B are partially unfolded or disordered in solution. The effect of C-terminal flexibility upon binding of two potent small molecule inhibitors to Cdc25B is then analyzed by using three structural models with variable levels of flexibility, including an equilibrium distributed ensemble of Cdc25B backbone conformations. The three Cdc25B structural models are used in combination with flexible docking, clustering, and calculation of binding free energies by the linear interaction energy approximation to construct and validate Cdc25B-inhibitor complexes. Two binding sites are identified on top and beside the Cdc25B active site. The diversity of interaction modes found increases with receptor flexibility. Backbone flexibility allows the formation of transient cavities or compact hydrophobic units on the surface of the stable, folded protein core that are unexposed or unavailable for ligand binding in rigid and densely packed crystal structures. The present results may help to speculate on the mechanisms of small molecule complexation to partially unfolded or locally disordered proteins.

Computer-aided design of a novel ligand for retinoic acid receptor in cancer chemotherapy

The isotypes of RAR and RXR are retinoic acid and retinoid X acid receptors, respectively, whose ligand-binding domain contains the ligand-dependent activation function, with distinct pharmacological targets for retinoids, involved in the treatment of various cancers and skin diseases. Due to the major challenge which cancer treatment and cure still imposes after many decades to the international scientific community, there is actually considerable interest in new ligands with increased bioactivity. We have focused on the retinoid acid receptor, which is considered an interesting target for drug design. In this work, we carried out density functional geometry optimizations, and different docking procedures. We performed screening in a large database (hundreds of thousands of molecules which we optimized at the AM1 level) yielding a set of potential bioactive ligands. A new ligand was selected and optimized at the B3LYP/6-31G* level. A flexible docking program was used to investigate the interactions between the receptor and the new ligand. The result of this work is compared with several crystallographic ligands of RAR. Our theoretically more bioactive new-ligand indicates stronger and more hydrogen bonds as well as hydrophobic interactions with the receptor. (c) 2005 Wiley Periodicals, Inc.

Modeling iron-catecholates binding to NGAL protein

Neutrophil gelatinase associated lipocalin (NGAL) protein is attracting a great interest because of its antibacterial properties played upon modulating iron content in competition against iron acquisition processes developed by pathogenic bacteria that bind selective ferric iron chelators (siderophores). Besides its known high affinity to enterobactin, the most important siderophore, it has been recently shown that NGAL is able to bind Fe(III) coordinated by catechols. The selective binding of Fe(III)-catechol ligands to NGAL is here studied by using iron coordination structures with one, two, and three catecholate ligands. By means of a computational approach that consists of B3LYP/6-311G(d,p) quantum calculations for geometries, electron properties and electrostatic potentials of ligands, protein–ligand flexible docking calculations, analyses of protein–ligand interfaces, and Poisson–Boltzmann electrostatic potentials for proteins, we study the binding of iron catecholate ligands to NGAL as a central member of the lipocalin family of proteins. This approach provides a modeling basis for exploring in silico the selective binding of iron catecholates ligands giving a detailed picture of their interactions in terms of electrostatic effects and a network of hydrogen bonds in the protein binding pocket.

Análise da interação entre moléculas desenhadas a partir do ácido anacárdico e a proteína PPAR usando ferramentas in silico

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Biológicas, Programa de Pós-Graduação em Biologia Molecular, 2016.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Synthesis, Binding and Bioactivity of [gamma]-Methylene [gamma]-Lactam Ecdysone Receptor Ligands: Advantages of QSAR Models for Flexible Receptors

Nuclear hormone receptors, such as the ecdysone receptor, often display a large amount of induced fit to ligands. The size and shape of the binding pocket in the EcR subunit changes markedly on ligand binding, making modelling methods such as docking extremely challenging. It is, however, possible to generate excellent 3D QSAR models for a given type of ligand, suggesting that the receptor adopts a relatively restricted number of binding site configurations or [`]attractors'. We describe the synthesis, in vitro binding and selected in vivo toxicity data for [gamma]-methylene [gamma]-lactams, a new class of high-affinity ligands for ecdysone receptors from Bovicola ovis (Phthiraptera) and Lucilia cuprina (Diptera). The results of a 3D QSAR study of the binding of methylene lactams to recombinant ecdysone receptor protein suggest that this class of ligands is indeed recognized by a single conformation of the EcR binding pocket.

Docking, molecular dynamics and QM/MM studies to delineate the mode of binding of CucurbitacinE to F-actin

CucurbitacinE (CurE) has been known to bind covalently to F-actin and inhibit depolymerization. However, the mode of binding of CurE to F-actin and the consequent changes in the F-actin dynamics have not been studied. Through quantum mechanical/molecular mechanical (QM/MM) and density function theory (DFT) simulations after the molecular dynamics (MD) simulations of the docked complex of F-actin and CurE, a detailed transition state (TS) model for the Michael reaction is proposed. The TS model shows nucleophilic attack of the sulphur of Cys257 at the beta-carbon of Michael Acceptor of CurE producing an enol intermediate that forms a covalent bond with CurE. The MD results show a clear difference between the structure of the F-actin in free form and F-actin complexed with CurE. CurE affects the conformation of the nucleotide binding pocket increasing the binding affinity between F-actin and ADP, which in turn could affect the nucleotide exchange. CurE binding also limits the correlated displacement of the relatively flexible domain 1 of F-actin causing the protein to retain a flat structure and to transform into a stable ``tense'' state. This structural transition could inhibit depolymerization of F-actin. In conclusion, CurE allosterically modulates ADP and stabilizes F-actin structure, thereby affecting nucleotide exchange and depolymerization of F-actin. (C) 2015 Elsevier Inc. All rights reserved.