Use of virtual screening, flexible docking, and molecular interaction fields to design novel HMG-CoA reductase inhibitors for the treatment of hypercholesterolemia

Dietary changes associated with drug therapy can reduce high serum cholesterol levels and dramatically decrease the risk of coronary artery disease, stroke, and overall mortality. Statins are hypolipemic drugs that are effective in the reduction of cholesterol serum levels, attenuating cholesterol synthesis in liver by competitive inhibition regarding the substrate or molecular target HMG-CoA reductase. We have herewith used computer-aided molecular design tools, i.e., flexible docking, virtual screening in large data bases, molecular interaction fields to propose novel potential HMG-CoA reductase inhibitors that are promising for the treatment of hypercholesterolemia.

Molecular dynamics, flexible docking, virtual screening, ADMET predictions, and molecular interaction field studies to design novel potential MAO-B inhibitors

Monoamine oxidase is a flavoenzyme bound to the mitochondrial outer membranes of the cells, which is responsible for the oxidative deamination of neurotransmitter and dietary amines. It has two distinct isozymic forms, designated MAO-A and MAO-B, each displaying different substrate and inhibitor specificities. They are the well-known targets for antidepressant, Parkinson`s disease, and neuroprotective drugs. Elucidation of the x-ray crystallographic structure of MAO-B has opened the way for the molecular modeling studies. In this work we have used molecular modeling, density functional theory with correlation, virtual screening, flexible docking, molecular dynamics, ADMET predictions, and molecular interaction field studies in order to design new molecules with potential higher selectivity and enzymatic inhibitory activity over MAO-B.

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.

Using Computer-aided Drug Design and Medicinal Chemistry Strategies in the Fight Against Diabetes

The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics. ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.

Computer-aided Drug Design of Novel PLA(2) Inhibitor Candidates for Treatment of Snakebite

Phospholipases A(2) (PLA(2)) are enzymes commonly found in snake venoms from Viperidae and Elaphidae families, which are major components thereof. Many plants are used in traditional medicine its active agents against various effects induced by snakebite. This article presents the PLA(2) BthTX-I structure prediction based on homology modeling. In addition, we have performed virtual screening in a large database yielding a set of potential bioactive inhibitors. A flexible docking program was used to investigate the interactions between the receptor and the new ligands. We have performed molecular interaction fields (MIFs) calculations with the phospholipase model. Results confirm the important role of Lys49 for binding ligands and suggest three additional residues as well. We have proposed a theoretically nontoxic, drug-like, and potential novel BthTX-I inhibitor. These calculations have been used to guide the design of novel phospholipase inhibitors as potential lead compounds that may be optimized for future treatment of snakebite victims as well as other human diseases in which PLA(2) enzymes are involved.

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.

Fast docking using the CHARMM force field with EADock DSS.

The prediction of binding modes (BMs) occurring between a small molecule and a target protein of biological interest has become of great importance for drug development. The overwhelming diversity of needs leaves room for docking approaches addressing specific problems. Nowadays, the universe of docking software ranges from fast and user friendly programs to algorithmically flexible and accurate approaches. EADock2 is an example of the latter. Its multiobjective scoring function was designed around the CHARMM22 force field and the FACTS solvation model. However, the major drawback of such a software design lies in its computational cost. EADock dihedral space sampling (DSS) is built on the most efficient features of EADock2, namely its hybrid sampling engine and multiobjective scoring function. Its performance is equivalent to that of EADock2 for drug-like ligands, while the CPU time required has been reduced by several orders of magnitude. This huge improvement was achieved through a combination of several innovative features including an automatic bias of the sampling toward putative binding sites, and a very efficient tree-based DSS algorithm. When the top-scoring prediction is considered, 57% of BMs of a test set of 251 complexes were reproduced within 2 Å RMSD to the crystal structure. Up to 70% were reproduced when considering the five top scoring predictions. The success rate is lower in cross-docking assays but remains comparable with that of the latest version of AutoDock that accounts for the protein flexibility. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011.

Combined Retrograde Flexible Ureteroscopic Lithotripsy with Holmium YAG Laser for Renal Calculi Associated with Ipsilateral Ureteral Stones

Purpose: The purpose of this study was to evaluate the effectiveness of combined ureteroscopic holmium YAG lithotripsy for renal calculi associated with ipsilateral ureteral stones. Materials and Methods: Between August 2002 and March 2007, retrograde flexible ureteroscopic stone treatment was attempted in 351 cases. Indication for treatment was concurrent symptomatic ureteral stones in 63 patients (group I). Additional operative time and perioperative complication rates were compared to a group of 39 patients submitted to ureteroscopic treatment for ureteral calculi exclusively (group II). Results: Mean ureteral stone size was 8.0 +/- 2.6 mm and 8.1 +/- 3.4 mm for groups I and II, respectively. Mean operative time for group I was 67.9 +/- 29.5 minutes and for group 2 was 49.3 +/- 13.2 minutes (p < 0.001). Flexible ureteroscopic therapy for renal calculi increased 18 minutes in the mean operative time. The overall complication rate was 3.1% and 2.5% for groups I and II, respectively (p = 0.87). Mean renal stone size was 10.7 +/- 6.4 mm, overall stone free rate in group I was 81%. However, considering only patients with renal stones smaller than 15 mm, the stone free rate was 88%. Successful treatment occurred in 81% of patients presenting lower pole stones, but only 76% of patients with multiple renal stones became stone free. As expected, stone free rate showed a significant negative correlation with renal stone size (p = 0.03; r = -0.36). Logistic regression model indicated an independent association of renal stones smaller than 15 mm and stone free rate (OR = 13.5; p = 0.01). Conclusion: Combined ureteroscopic treatment for ureteral and ipsilateral renal calculi is a safe and attractive option for patients presenting for symptomatic ureteral stone and ipsilateral renal calculi smaller than 15 mm.