Computational study of human phosphomannose isomerase: Insights from homology modeling and molecular dynamics simulation of enzyme bound substrate

Phosphomannose isomerase is a zinc metalloenzyme that catalyzes the reversible isomerization of mannose-6-phosphate and fructose-6-phosphate, and the three-dimensional (3D) structure of human phosphomannose isomerase has not been reported. In order to understand the catalytic mechanism, the 3D structure of the protein is built by using homology modeling based on the known crystal structure of mannose-6-phosphate isomerase from (PDB code 1PMI). The model structure is further refined by energy minimization and molecular dynamics methods. The mannose-6-phosphate-enzyme complex is developed by molecular docking and the key residues involved in the ligand binding are determined, which will facilitate the understanding of the action mode of the ligands and guide further genetic studies. Our results suggest a hydride transfer mechanism of alpha-hydrogen between the C1 and C2 positions but do not support the cis-enediol mechanism. The detailed mechanism involves, on one side, Zn2+ mediating the movement of a proton between O1 and O2, and, on the other side, the hydrophobic environment formed in part by Tyr278 promoting transfer of a hydride ion.     

A systematic methodology for large scale compound screening: A case study on the discovery of novel S1PL inhibitors

Decrease in sphingosine 1-phosphate (S1P) concentration induces migration of pathogenic T cells to the blood stream, disrupts the CNS and it is implicated in multiple sclerosis (MS), a progressive inflammatory disorder of the central nervous system (CNS), and Alzheimer’s disease (AD). A promising treatment alternative for MS and AD is inhibition of the activity of the microsomal enzyme sphingosine 1-phosphate lyase (S1PL), which degrades intracellular S1P. This report describes an integrated systematic approach comprising virtual screening, molecular docking, substructure search and molecular dynamics simulation to discover novel S1PL inhibitors. Virtual screening of the ZINC database via ligand-based and structure-based pharmacophore models yielded 10000 hits. After molecular docking, common substructures of the top ranking hits were identified. The ligand binding poses were optimized by induced fit docking. MD simulations were performed on the complex structures to determine the stability of the S1PL-ligand complex and to calculate the binding free energy. Selectivity of the selected molecules was examined by docking them to hERG and cytochrome P450 receptors. As a final outcome, 15 compounds from different chemotypes were proposed as potential S1PL inhibitors. These molecules may guide future medicinal chemistry efforts in the discovery of new compounds against the destructive action of pathogenic T cells.     

Pharmacophore identification and virtual screening for methionyl-tRNA synthetase inhibitors

Aminoacyl-tRNA synthetases (aaRSs) are essential enzymes involved in protein biosynthesis in all living organisms and are an unexploited antibacterial targets, as many strains of bacteria have become resistant to all established classes of antibiotics. Therefore, the main aim of this study is to discover new lead molecules which would be useful as anti-bacterial compounds. Pharmacophore models were developed by using CATALYST HypoGen with a training set of 29 diverse methionyl-tRNA synthetase (MetRS) inhibitors. The best quantitative pharmacophore hypothesis (Hypo1) obtained a correlation coefficient of 0.975, root mean square deviation (RMSD) of 0.55 and cost difference (null cost-total cost) of 70.32. This Hypo1 was validated by two methods, first by using 104 test set molecules which resulted a correlation of 0.926 between HypoGen estimated activities versus experimental activities and secondly by Cat-Scramble validation method. This validated pharmacophore model was further used for screening databases for discovery of new MetRS inhibitors. The new lead compounds were further analyzed for drug-like properties. Homology modeled structure of Staphylococcus aureus MetRS was built and molecular docking studies were performed with many inhibitors using the newly built protein structure. Finally, it was found that the new leads exhibited good estimated inhibitory activity, calculated binding properties similar to experimentally proven compounds and also favorable drug-like properties.     

In silico screening and study of novel ERK2 inhibitors using 3D QSAR,docking and molecular dynamics

ERK2 is a dual specificity protein kinase, part of the Ras/Raf/MEK/ERK signal transduction cascade. It forms an interesting target for inhibition based on its relationship with cell proliferation and oncogenesis. A 3D QSAR pharmacophore model (Hypo1) with high correlation (r = 0.938) was developed for ERK2 ATP site on the basis of experimentally known inhibitors. The model included three hydrogen bonds, and one hydrophobic site. Assessment of Hypo1 through Fisher randomization, cost analysis, leave one out method and decoy test suggested that the model can reliably detect ERK2 inhibitors. Hypo1 has been used for virtual screening of potential inhibitors from ZINC, Drug Bank, NCI, Maybridge and Chembank databases. Using Hypo1 as a query, databases have been interrogated for compounds who meet the pharmacophore features. The resulting hit compounds were subject to docking and analysis. Docking and molecular dynamics analysis showed that in order to achieve a higher potency compounds have to interact with catalytic site, glycine rich loop, Hinge region, Gatekeeper region and ATP site entrance residues. We also identified catalytic site and Glycine rich loop as important regions to bind by molecules for better potency and selectivity.     

LCC的分子模型化方法研究进展（1987—1999）

总结了十多年来ＬＣＣ实验室在分子模型化方面的主要研究进展。文章分为６个方面：（１）结构数据库的引进、开发、和推广应用：（２）支持结构优化的方法研究和软件开发;（３）虚拟受体模型方法;（４）用于发现新先导的药效团搜索方法和软件开发;（５）新算法的创立;（６）科学数据库中结构与性质信息的集成。     

Discovery of potent inhibitor for matrix metalloproteinase-9 by pharmacophore based modeling and dynamics simulation studies

Matrix metalloproteinase-9 (MMP-9) is an attractive target for anticancer therapy. In the present study ligand based pharmacophore modeling was performed to elucidate the structural elements for a diverse class of MMP-9 inhibitors. The pharmacophore model was validated through Güner-Henry (GH) scoring method. The final pharmacophore model consisted of three hydrogen bond acceptors (HBA), and two ring aromatic regions (RA). This model was utilized to screen the natural compound database to seek novel compounds as MMP-9 inhibitors. The identified hits were validated using molecular docking and molecular dynamics simulation studies. Finally, one compound named Hinokiflavone from Juniperus communis had high binding free energy of −26.54 kJ/mol compared with the known inhibitors of MMP-9. Cytotoxicity for hinokiflavone was evaluated by MTT assay. Inhibition of MMP-9 in the presence of hinokiflavone was detected by gelatin zymography and gelatinolytic inhibition assay. Results revealed that the natural compounds derived based on the developed pharmacophore model would be useful for further design and development of MMP-9 inhibitors.     

Exploring the P2 and P3 ligand binding features for hepatitis C virus NS3 protease using some 3D QSAR techniques

Several three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and catalyst pharmacophore feature building programs for a series of 26 truncated ketoacid inhibitors designed particularly for exploring the P2 and P3 binding pockets of HCV NS3 protease. The structures of these inhibitors were built from a structure template extracted from the crystal structure of HCV NS3 protease. The structures were aligned through docking each inhibitor into the NS3 active site using program GOLD. The best CoMSIA model was identified from the stepwise analysis results and the corresponding pharmacophore features derived were used for constructing a pharmacophore hypothesis by the catalyst program. Pharmacophore features obtained by CoMFA and CoMSIA are found to be in accord with each other and are both mapped onto the molecular 5K surface of NS3 active site. These pharmacophore features were also compared with those obtained by the catalyst program and mapped onto the same NS3 molecular surface. The pharmacophore building process was also performed for 20 boronic acid based NS3 inhibitors characterized by a long hydrophobic side chain attached at position P2. This latter pharmacophore hypothesis built by the catalyst program was also mapped onto the molecular surface of NS3 active site to define a second hydrophobic feature at position P2. The possibility of using the pharmacophore features mapped P2 and P3 binding pocket to design more potent depeptidized NS3 inhibitors was discussed.     

In silico identification of novel inhibitors against Plasmodium falciparum dihydroorate dehydrogenase

Plasmodium falciparum causes the most fatal form of malaria and accounts for over 1 million deaths annually, yet currently used drug therapies are compromised by resistance. The malaria parasite cannot salvage pyrimidines and relies on de novo biosynthesis for survival. The enzyme dihydrooratate dehydrogenase (DHODH), a mitochondrial flavoenzyme, catalyzes the rate-limiting step of this pathway and is therefore an attractive anti-malarial chemotherapeutic target. In an effort to design new and potential anti-malarials, structure-based pharmacophore mapping, molecular docking, binding energy calculations and binding affinity predictions were employed in a virtual screening strategy to design new and potent P. falciparum dihydrooratate dehydrogenase (PfDHODH) inhibitors. A structure-based pharmacophore model was generated which consist of important interactions as observed in co-crystal of PfDHODH enzyme. The developed model was used to retrieve molecules from ChemBridge database, a freely available commercial database. A total of 87 molecules mapped on the modeled pharmacophore from the database. The retrieved hits were further screened by docking simulation, binding energy calculations and biding affinity predictions using genetic optimization for ligand docking (GOLD) and MOE. Based on these results, finally 26 chemo-types molecules were predicted as new, potential and structurally diverse PfDHODH inhibitors.     

Discovery of high affinity ligands for β2-adrenergic receptor through pharmacophore-based high-throughput virtual screening and docking

Novel high affinity compounds for human β₂-adrenergic receptor (β₂-AR) were searched among the clean drug-like subset of ZINC database consisting of 9,928,465 molecules that satisfy the Lipinski's rule of five. The screening protocol consisted of a high-throughput pharmacophore screening followed by an extensive amount of docking and rescoring. The pharmacophore model was composed of key features shared by all five inactive states of β₂-AR in complex with inverse agonists and antagonists. To test the discriminatory power of the pharmacophore model, a small-scale screening was initially performed on a database consisting of 117 compounds of which 53 antagonists were taken as active inhibitors and 64 agonists as inactive inhibitors. Accordingly, 7.3% of the ZINC database subset (729,413 compounds) satisfied the pharmacophore requirements, along with 44 antagonists and 17 agonists. Afterwards, all these hit compounds were docked to the inactive apo form of the receptor using various docking and scoring protocols. Following each docking experiment, the best pose was further evaluated based on the existence of key residues for antagonist binding in its vicinity. After final evaluations based on the human intestinal absorption (HIA) and the blood brain barrier (BBB) penetration properties, 62 hit compounds have been clustered based on their structural similarity and as a result four scaffolds were revealed. Two of these scaffolds were also observed in three high affinity compounds with experimentally known K_i values. Moreover, novel chemical compounds with distinct structures have been determined as potential β₂-AR drug candidates.     

基于ALS抑制剂药效团模型的数据库搜索

以ALS抑制剂药效团模型为基础建立了提问结构,将药效团模型中的生物结构信息输入到多种小分子三维结构数据库中(NCI-3D和ACD-3D数据库),借助分子三维结构搜索软件(3DFS和ISIS/3D软件)和多种搜索方法(POW-ELL方法和遗传算法)分别搜寻出100多个符合特征结构信息的全新结构候选化合物。这些命中结构的分子特征信息为我们下一步进行分子设计,确定先导化合物结构明确了方向,并提供了重要依据。     

Computational investigation of interactions between human H2 receptor and its agonists

Type 2 histamine receptor (H(2)R) is widely distributed in the body. Its main function is modulating the secretion of gastric acid. Most gastric acid-related diseases are closely associated with it. In this study, a combination of pharmacophore modeling, homology modeling, molecular docking and molecular dynamics methods were performed on human H(2)R and its agonists to investigate interaction details between them. At first, a pharmacophore model of H(2)R agonists was developed, which was then validated by QSAR and database searching. Afterwards, a model of the H(2)R was built utilizing homology modeling method. Then, a reference agonist was docked into the receptor model by induced fit docking. The 'induced' model can dramatically improve the recovery ratio from 46.8% to 69.5% among top 10% of the ranked database in the simulated virtual screening. The pharmocophore model and the receptor model matched very well each other, which provided valuable information for future studies. Asp98, Asp186 and Tyr190 played key roles in the binding of H(2)R agonists, and direct interactions were observed between the three residues and agonists. Residue Tyr250 could also form a hydrogen bond with H(2)R agonists. These findings would be very useful for the discovery of novel and potent H(2)R agonists.     

Identification of potent urease inhibitors via ligand- and structure-based virtual screening and in vitro assays

A pharmacophore model was developed based on three structurally diverse urease inhibitors by using the GASP program. This model comprises the positions and tolerance for two acceptor atoms (AA1 and AA2), one donor atom (DA1), and one hydrophobic center (HYP1). This derived phamacophore model was employed to screen an in-house database of organic compounds. Hits obtained were evaluated by molecular docking using GOLD software. On the basis of ligand- and structural-based predictions, an in vitro testing of short-listed compounds was conducted and a novel class of urease inhibitors (2-aminothiophines) was identified. The potent in vitro activity and selectivity of these compounds, along with their non-toxic nature against the plant cells indicated that they can serve as leads for solving urease-associated health and agriculture problems.     

Binding mode analyses and pharmacophore model development for sulfonamide chalcone derivatives,a new class of α-glucosidase inhibitors

Sulfonamide chalcone derivatives are a new class of non-saccharide compounds that effectively inhibit glucosidases which are the major targets in the treatment of Type 2 diabetes and HIV infection. Our aim is to explore their binding mode of interaction at the active site by comparing with the sugar derivatives and to develop a pharmacophore model which would represent the critical features responsible for α-glucosidase inhibitory activity. The homology modeled structure of Saccharomyces cerevisiae α-glucosidase was built and used for molecular docking of non-sugar/sugar derivatives. The validated docking results projected the crucial role of NH group in the binding of sugar/non-sugar derivatives to the active site. Ligplot analyses revealed that Tyr71, and Phe177 form hydrophobic interactions with sugar/non-sugar derivatives by holding the terminal glycosidic ring mimics. Molecular dynamic (MD) simulation studies were performed for protein alone and with chalcone derivative to prove its binding mechanism as shown by docking/Ligplot results. It would also help to substantiate the homology modeled structure stability. With the knowledge of the crucial interactions between ligand and protein from docking and MD simulation studies, features for pharmacophore model development were chosen. The CATALYST/HipHop was used to generate a five featured pharmacophore model with a training set of five non-sugar derivatives. As validation, all the crucial features of the model were perfectly mapped onto the 3D structures of the sugar derivatives as well as the newly tested non-sugar derivatives. Thus, it can be useful in virtual screening for finding new non-sugar derivatives as α-glucosidase inhibitors.     

Binding mode analyses and pharmacophore model development for sulfonamide chalcone derivatives, a new class of alpha-glucosidase inhibitors

Sulfonamide chalcone derivatives are a new class of non-saccharide compounds that effectively inhibit glucosidases which are the major targets in the treatment of Type 2 diabetes and HIV infection. Our aim is to explore their binding mode of interaction at the active site by comparing with the sugar derivatives and to develop a pharmacophore model which would represent the critical features responsible for alpha-glucosidase inhibitory activity. The homology modeled structure of Saccharomyces cerevisiae alpha-glucosidase was built and used for molecular docking of non-sugar/sugar derivatives. The validated docking results projected the crucial role of NH group in the binding of sugar/non-sugar derivatives to the active site. Ligplot analyses revealed that Tyr71, and Phe177 form hydrophobic interactions with sugar/non-sugar derivatives by holding the terminal glycosidic ring mimics. Molecular dynamic (MD) simulation studies were performed for protein alone and with chalcone derivative to prove its binding mechanism as shown by docking/Ligplot results. It would also help to substantiate the homology modeled structure stability. With the knowledge of the crucial interactions between ligand and protein from docking and MD simulation studies, features for pharmacophore model development were chosen. The CATALYST/HipHop was used to generate a five featured pharmacophore model with a training set of five non-sugar derivatives. As validation, all the crucial features of the model were perfectly mapped onto the 3D structures of the sugar derivatives as well as the newly tested non-sugar derivatives. Thus, it can be useful in virtual screening for finding new non-sugar derivatives as alpha-glucosidase inhibitors.     

Selective pharmacophore design for alpha1-adrenoceptor subtypes

Alpha1-adrenoceptors are G-protein coupled receptors found in a variety of vascular tissues and responsible for vasoconstriction. Selectivity for each of the three subtypes is an important consideration in drug design in order to minimise the possibility of side effects. Using Catalyst we developed ligand-based pharmacophores from alpha(1a,b,d)-selective antagonists available in the literature using three separate training sets. Four-feature pharmacophores were developed for the alpha(1a) and alpha(1b) subtype-selective antagonists and a five-feature pharmacophore was developed for the alpha(1d) subtype-selective antagonists. The alpha(1a) pharmacophore represents both class I and II compounds with good predictivity for other compounds outside the training set as well. The alpha(1b) pharmacophore best predicts the activity of prazosin analogues as these make up the majority of alpha(1b)-selective antagonists. Unexpectedly, no positive ionisable feature was incorporated in the alpha(1b) pharmacophore. The alpha(1d) pharmacophore was based primarily on one structural class of compounds, but has good predictivity for a heterogeneous test set. Preliminary docking studies using AutoDock and optimised alpha1-adrenoceptor homology models, conducted with the antagonists prazosin (32) and 66, showed good agreement with the findings from the pharmacophores.     

Strategies for generating less toxic P-selectin inhibitors: pharmacophore modeling, virtual screening and counter pharmacophore screening to remove toxic hits

This paper describes the generation of ligand-based as well as structure-based models and virtual screening of less toxic P-selectin receptor inhibitors. Ligand-based model, 3D-pharmacophore was generated using 27 quinoline salicylic acid compounds and is used to retrieve the actives of P-selectin. This model contains three hydrogen bond acceptors (HBA), two ring aromatics (RA) and one hydrophobic feature (HY). To remove the toxic hits from the screened molecules, a counter pharmacophore model was generated using inhibitors of dihydrooratate dehydrogenase (DHOD), an important enzyme involved in nucleic acid synthesis, whose inhibition leads to toxic effects. Structure-based models were generated by docking and scoring of inhibitors against P-selectin receptor, to remove the false positives committed by pharmacophore screening. The combination of these ligand-based and structure-based virtual screening models were used to screen a commercial database containing 538,000 compounds.     

Comparison and analysis of the structures and binding modes of antifungal SE and CYP51 inhibitors

With the abuse of clinical broad-spectrum antimicrobial agents, immunosuppressive agents, chemotherapy drugs, the emergence of pathogenic fungi resistance is more and more frequent. However, there is still no effective treatment for the fungal resistance. Squalenee epoxidase (SE) and 14 α-demethylase (CYP51) are important antifungal drug targets. In order to achieve a deeper insight into the structural characteristics and the action modes of SE and CYP51inhibitors, the homology model of SE (Candida albicans) was constructed using monooxygenase of Pseudomonas aeruginosa as template, and the reliability of model was confirmed by Ramachandran plots and Verify 3D. Subsequently, the molecular superimposition and molecular docking were performed, and the pharmacophore model based on the CYP51 receptor structure was constructed. The results indicate that SE and CYP51 inhibitors have common structural feature with two parts of essential fragments, which are mainly composed of aromatic groups. In addition, the fragment structures of inhibitors are combined in the similar hydrophobic pockets through the hydrophobic forces. The present study provides a deeper perspective to understand the characteristics and docking modes of SE and CYP51 inhibitors. It can be used to guide the optimization and design of SE and CYP51 inhibitors. In addition, it also provides the oretical support for the development of dual target antifungal inhibitors (SE and CYP51), which can help us solve the problem of fungi resistance.     

Homology modelling,docking, pharmacophore and site directed mutagenesis analysis to identify the critical amino acid residue of PknI from Mycobacterium tuberculosis

Tuberculosis is caused by Mycobacterium tuberculosis, an intracellular pathogen. PknI is one of the 11 functional Serine/Threonine Protein Kinases which is predicted to regulate the cell division of M. tuberculosis. In order to find newer drugs and vaccine we need to understand the pathogenesis of the disease. We have used the bioinformatics approach to identify the functionally active residues of PknI and to confirm the same with wet lab experiments. In the current study, we have created homology model for PknI and have done comparative structural analysis of PknI with other kinases. Molecular docking studies were done with a library of kinase inhibitors and T95 was found as the potent inhibitor for PknI. Based on structure based pharmacophore analysis of kinase substrate complexes, Lys 41 along with Asp90, Val92 and Asp96 were identified as functionally important residues. Further, we used site directed mutagenesis technique to mutate Lys 41 to Met resulting in defective cell division of Mycobacterium smegmatis mc². Overall, the proposed model together with its binding features gained from pharmacophore docking studies helped in identifying ligand inhibitor specific to PknI which was confirmed by laboratory experiments.     

Long range molecular dynamics study of interactions of the eukaryotic glucosamine-6-phosphate synthase with fructose-6-phosphate and UDP-GlcNAc

Glucosamine-6-phosphate synthase (EC 2.6.1.16) is responsible for catalysis of the first and practically irreversible step in hexosamine metabolism. The final product of this pathway, uridine 5′ diphospho N-acetyl-d-glucosamine (UDP-GlcNAc), is an essential substrate for assembly of bacterial and fungal cell walls. Moreover, the enzyme is involved in phenomenon of hexosamine induced insulin resistance in type II diabetes, which makes of it a potential target for anti-fungal, anti-bacterial and anti-diabetic therapy.The crystal structure of isomerase domain from human pathogenic fungus Candida albicans has been solved recently but it doesn’t reveal the molecular mechanism details of inhibition taking place under UDP-GlcNAc influence, the unique feature of eukaryotic enzyme. The following study is a continuation of the previous research based on comparative molecular dynamics simulations of the structures with and without the enzyme's physiological inhibitor (UDP-GlcNAc) bound. The models used for this study included fructose-6-phosphate, one of the enzyme's substrates in its binding pocket.The simulation results studies demonstrated differences in mobility of the compared structures. Some amino acid residues were determined, for which flexibility is evidently different between the models. Importantly, it has been confirmed that the most fixed residues are related to the inhibitor binding process and to the catalysis reaction. The obtained results constitute an important step towards understanding of the inhibition that GlcN-6-P synthase is subjected by UDP-GlcNAc molecule.