Alphavirus protease inhibitors from natural sources: A homology modeling and molecular docking investigation

Alphaviruses such as Chikungunya virus (CHIKV), O’Nyong–Nyong virus (ONNV), Ross River virus (RRV), Eastern equine encephalitis virus (EEEV), Venezuelan equine encephalitis virus (VEEV), and Western equine encephalitis virus (WEEV), are mosquito-transmitted viruses that can cause fevers, rash, and rheumatic diseases (CHIKV, ONNV, RRV) or potentially fatal encephalitis (EEEV, VEEV, WEEV) in humans. These diseases are considered neglected tropical diseases for which there are no current antiviral therapies or vaccines available. The alphavirus non-structural protein 2 (nsP2) contains a papain-like protease, which is considered to be a promising target for antiviral drug discovery. In this work, molecular docking analyses have been carried out on a library of 2174 plant-derived natural products (290 alkaloids, 664 terpenoids, 1060 polyphenolics, and 160 miscellaneous phytochemicals) with the nsP2 proteases of CHIKV, ONNV, RRV, EEEV, VEEV, WEEV, as well as Aura virus (AURV), Barmah Forest Virus (BFV), Semliki Forest virus (SFV), and Sindbis virus (SINV) in order to identity structural scaffolds for inhibitor design or discovery. Of the 2174 phytochemicals examined, a total of 127 showed promising docking affinities and poses to one or more of the nsP2 proteases, and this knowledge can be used to guide experimental investigation of potential inhibitors.     

Homology modeling,docking and structure-based pharmacophore of inhibitors of DNA methyltransferase

DNA methyltransferase 1 (DNMT1) is an emerging epigenetic target for the treatment of cancer and other diseases. To date, several inhibitors from different structural classes have been published. In this work, we report a comprehensive molecular modeling study of 14 established DNTM1 inhibitors with a herein developed homology model of the catalytic domain of human DNTM1. The geometry of the homology model was in agreement with the proposed mechanism of DNA methylation. Docking results revealed that all inhibitors studied in this work have hydrogen bond interactions with a glutamic acid and arginine residues that play a central role in the mechanism of cytosine DNA methylation. The binding models of compounds such as curcumin and parthenolide suggest that these natural products are covalent blockers of the catalytic site. A pharmacophore model was also developed for all DNMT1 inhibitors considered in this work using the most favorable binding conformations and energetic terms of the docked poses. To the best of our knowledge, this is the first pharmacophore model proposed for compounds with inhibitory activity of DNMT1. The results presented in this work represent a conceptual advance for understanding the protein–ligand interactions and mechanism of action of DNMT1 inhibitors. The insights obtained in this work can be used for the structure-based design and virtual screening for novel inhibitors targeting DNMT1.     

Pharmacophore modeling,atom based 3D-QSAR,molecular docking and molecular dynamics studies on Escherichia coli ParE inhibitors

ATP dependent ParE enzyme is as an attractive target for the development of antibacterial agents. Atom based 3D-QSAR model AADHR.187 was developed based on the thirty eight Escherichia coli ParE inhibitors. The generated model showed statistically significant coefficient of determinations for the training (R² = 0.985) and test (R² = 0.86) sets. The cross-validated correlation coefficient (q2) was 0.976. The utility of the generated model was validated by the enrichment study. The model was also validated with structurally diverse external test set of ten compounds. Contour plot analysis of the generated model unveiled the chemical features necessary for the E. coli ParE enzyme inhibition. Extra-precision docking result revealed that hydrogen bonding and ionic interactions play a major role in ParE protein-ligand binding. Binding free energy was computed for the data set inhibitors to validate the binding affinity. A 30-ns molecular dynamics simulation showed high stability and effective binding of inhibitor 34 within the active site of ParE enzyme. Using the best fitted model AADHR.187, pharmacophore-based high-throughput virtual screening was performed to identify virtual hits. Based on the above studies three new molecules are proposed as E. coli ParE inhibitors with high binding affinity and favourable ADME properties.     

Design and synthesis of sulfur based inhibitors of matrix metalloproteinase-1

Fibroblast collagenase (MMP-1), a member of the matrix metalloproteinases family, is believed to be a pathogenesis of arthritis, by cleaving triple-helical type II collagen in cartilage. From the similarity of the active site zinc binding mode with hydroxamate, we designed and synthesized alpha-mercaptocarbonyl possessing compounds (3-5), which incorporated various peptide sequences as enzyme recognition sites. The P4-P1 peptide incorporating compound (3) exhibited as potent inhibition as the hydroxamate (1) and the carboxylate (2) type inhibitors, with an IC50 of 10(-6) M order against MMP-1. But the inhibitor (3) related compounds (6-8) displayed decreased or no inhibitory potencies. These results suggest that the existence of both the carbonyl and thiol groups might be critical for the inhibition, and the distance between the two functional groups is important for inhibitory potency. For Pn' peptide incorporating compounds (4a-k), except for 4h and 4k, all compounds showed IC50 values under sub-nanomolar. Among them, for potent inhibition, Leu was better than Phe and Val as the P1' amino acid, and the P2' position amino acid was necessary, and preferentially Phe. Insertion of the Pn peptide into 4d or 4k, giving compounds 5a-c, did not increase the activities of 4d and 4k. Substitution of the mercapto group with other functional groups lost the activity of compound 4a. The stereochemical preference at the thiol-attached position was also determined by preparation of both isomers of 4a. It was found that the S configuration compound (36b) is approximately 100 times more potent than the corresponding R-isomer (36a).     

Pharmacophore modeling,virtual screening and molecular docking of ATPase inhibitors of HSP70

Heat shock protein 70 is an effective anticancer target as it influences many signaling pathways. Hence the study investigated the important pharmacophore feature required for ATPase inhibitors of HSP70 by generating a ligand based pharmacophore model followed by virtual based screening and subsequent validation by molecular docking in Discovery studio V4.0. The most extrapolative pharmacophore model (hypotheses 8) consisted of four hydrogen bond acceptors. Further validation by external test set prediction identified 200 hits from Mini Maybridge, Drug Diverse, SCPDB compounds and Phytochemicals. Consequently, the screened compounds were refined by rule of five, ADMET and molecular docking to retain the best competitive hits. Finally Phytochemical compounds Muricatetrocin B, Diacetylphiladelphicalactone C, Eleutheroside B and 5-(3-{[1-(benzylsulfonyl)piperidin-4-yl]amino}phenyl)- 4-bromo-3-(carboxymethoxy)thiophene-2-carboxylic acid were obtained as leads to inhibit the ATPase activity of HSP70 in our findings and thus can be proposed for further in vitro and in vivo evaluation.     

Pharmacophore model-aided virtual screening combined with comparative molecular docking and molecular dynamics for identification of marine natural products as SARS-CoV-2 papain-like protease inhibitors

Targeting SARS-CoV-2 papain-like protease using inhibitors is a suitable approach for inhibition of virus replication and dysregulation of host anti-viral immunity. Engaging all five binding sites far from the catalytic site of PLpro is essential for developing a potent inhibitor. We developed and validated a structure-based pharmacophore model with 9 features of a potent PLpro inhibitor. The pharmacophore model-aided virtual screening of the comprehensive marine natural product database predicted 66 initial hits. This hit library was downsized by filtration through a molecular weight filter of ≤ 500 g/mol. The 50 resultant hits were screened by comparative molecular docking using AutoDock and AutoDock Vina. Comparative molecular docking enables benchmarking docking and relieves the disparities in the search and scoring functions of docking engines. Both docking engines retrieved 3 same compounds at different positions in the top 1 % rank, hence consensus scoring was applied, through which CMNPD28766, aspergillipeptide F emerged as the best PLpro inhibitor. Aspergillipeptide F topped the 50-hit library with a pharmacophore-fit score of 75.916. Favorable binding interactions were predicted between aspergillipeptide F and PLpro similar to the native ligand XR8-24. Aspergillipeptide F was able to engage all the 5 binding sites including the newly discovered BL2 groove, site V. Molecular dynamics for quantification of Cα-atom movements of PLpro after ligand binding indicated that it exhibits highly correlated domain movements contributing to the low free energy of binding and a stable conformation. Thus, aspergillipeptide F is a promising candidate for pharmaceutical and clinical development as a potent SARS-CoV-2 PLpro inhibitor.     

Insights into the key structural features of triazolothienopyrimidines as anti-HIV agents using QSAR,molecular docking,and pharmacophore modeling

Structural Chemistry - The development of severe drug resistance caused by the extensive use of anti-HIV agents has resulted in resistance mutation that compromise efficacy of anti-retroviral. We...     

Discovery of novel Pim-1 kinase inhibitors by a hierarchical multistage virtual screening approach based on SVM model, pharmacophore, and molecular docking

In this investigation, we describe the discovery of novel potent Pim-1 inhibitors by employing a proposed hierarchical multistage virtual screening (VS) approach, which is based on support vector machine-based (SVM-based VS or SB-VS), pharmacophore-based VS (PB-VS), and docking-based VS (DB-VS) methods. In this approach, the three VS methods are applied in an increasing order of complexity so that the first filter (SB-VS) is fast and simple, while successive ones (PB-VS and DB-VS) are more time-consuming but are applied only to a small subset of the entire database. Evaluation of this approach indicates that it can be used to screen a large chemical library rapidly with a high hit rate and a high enrichment factor. This approach was then applied to screen several large chemical libraries, including PubChem, Specs, and Enamine as well as an in-house database. From the final hits, 47 compounds were selected for further in vitro Pim-1 inhibitory assay, and 15 compounds show nanomolar level or low micromolar inhibition potency against Pim-1. In particular, four of them were found to have new scaffolds which have potential for the chemical development of Pim-1 inhibitors.     

A combined structure-based pharmacophore modeling and 3D-QSAR study on a series of N-heterocyclic scaffolds to screen novel antagonists as human DHFR inhibitors

Structural Chemistry - Dihydrofolate reductase (DHFR) is an essential enzyme that participates in folate metabolism and purine and thymidylate synthesis in cell proliferation. It converts...     

Discovery of potentially biased agonists of mu-opioid receptor (MOR) through molecular docking,pharmacophore modeling,and MD simulation

Opioids are well known for their potent analgesic efficacy and severe side effects. Studies have shown that analgesic effects are mediated by the downstream G-protein-dependent pathway of the μ-opioid receptor (MOR), and another β-arrestin-dependent pathway mediates side effects such as respiratory depression, constipation and tolerance etc. TRV130 is a biased ligand for G-protein-dependent pathway, which has high analgesia and has fewer side effects than morphine. In this study, the structure similarity search was performed on the IBSSC database using Oliceridine (TRV130) and PZM21 as templates. The 3D structure-based pharmacophore model was built and combined molecular docking prediction mode was selected to filter out small molecules, Finally, based on affinity prediction, four candidate molecules were obtained. Molecular dynamics simulations explored the detailed interaction mechanism of proteins with small molecules under dynamics. These results suggest that these candidate molecules are potential MOR agonists.     

Discovery of potential M2 channel inhibitors based on the amantadine scaffold via virtual screening and pharmacophore modeling

The M2 channel protein on the influenza A virus membrane has become the main target of the anti-flu drugs amantadine and rimantadine. The structure of the M2 channel proteins of the H3N2 (PDB code 2RLF) and 2009-H1N1 (Genbank accession number GQ385383) viruses may help researchers to solve the drug-resistant problem of these two adamantane-based drugs and develop more powerful new drugs against influenza A virus. In the present study, we searched for new M2 channel inhibitors through a combination of different computational methodologies, including virtual screening with docking and pharmacophore modeling. Virtual screening was performed to calculate the free energies of binding between receptor M2 channel proteins and 200 new designed ligands. After that, pharmacophore analysis was used to identify the important M2 protein-inhibitor interactions and common features of top binding compounds with M2 channel proteins. Finally, the two most potential compounds were determined as novel leads to inhibit M2 channel proteins in both H3N2 and 2009-H1N1 influenza A virus.     

Predicting hiCE inhibitors based upon pharmacophore models derived from the receptor and its ligands

Human intestinal carboxyl esterase (hiCE) is a drug target for ameliorating irinotecan-induced diarrhea. By reducing irinotecan-induced diarrhea, hiCE inhibitors can improve the anti-cancer efficacy of irinotecan. To find effective hiCE inhibitors, a new virtual screening protocol that combines pharmacophore models derived from the hiCE structure and its ligands has been proposed. The hiCE structure has been constructed through homology techniques using hCES1’s crystal structure. The hiCE structure was optimized via molecular dynamics simulations with the most known active hiCE inhibitors docked into the structure. An optimized pharmacophore, derived from the receptor, was then generated. A ligand-based pharmacophore was also generated from a larger set of known hiCE inhibitors. The final hiCE inhibitor predictions were based upon the virtual screening hits from both ligand-based and receptor-based pharmacophore models. The hit rates from the ligand-based and receptor-based pharmacophore models are 88% and 86%, respectively. The final hit rate is 94%. The two models are highly consistent with one another (85%). This proves that both models are reliable.     

A comparative docking study and the design of potentially selective MMP inhibitors

As part of a program aimed at the design and synthesis of constrained MMP inhibitors, a survey of the reported X-ray and NMR structures of MMP/inhibitor complexes was performed, revealing mutations of key amino acids at different subsites between MMPs. A comparative study of fully automated docking programs AutoDock and DOCK in closely approximating the X-ray crystal structures of ten selected MMP inhibitors was performed. AutoDock proved to be highly reliable, efficient and predictive for a set of inhibitors with less than six atom types.     

Microwave assisted ring-opening of epoxides with N-biaryl sulfonamides in the synthesis of matrix metalloproteinase-9 inhibitors

A microwave accelerated epoxide ring-opening process with N-biaryl sulfonamides is described. Under this mild, highly efficient condition, an α-hydroxy-β-N-biaryl sulfonamide skeleton is rapidly assembled leading ultimately to a novel series of matrix metalloproteinase-9 inhibitors with single digit nanomolar activities.     

Design of selective TACE inhibitors using molecular docking studies: Synthesis and preliminary evaluation of anti-inflammatory and TACE inhibitory activity

Tumor necrosis factor-α (TNF-α) converting enzyme (TACE) has been considered one of the principal therapeutic targets for the treatment of TNF-dependent pathologies. Several TACE inhibitors have been reported, but none of them has been successfully passed to phase II clinical trials. In the present work, we attempted to design highly selective new non-hydroxamate sulfonamide TACE inhibitors. The docking study was performed on one of the crystal structures of TACE, selected based on its resolution and R value, to tackle the flexibility issue of the active site. The results allowed us to distinguish the analogues with a higher binding affinity toward the active site of TACE and to identify the substituent of analogues needed for binding with the surrounding site of the enzyme. Finally the analogues were docked on crystal structures of six different matrix metalloproteinases (MMPs) for a selectivity study of TACE over MMPs. Some of these analogues were synthesized and subjected to preliminary testing for in vivo anti-inflammatory activity and TACE inhibitory activity.     

Molecular structural investigations of quinoxaline derivatives through 3D-QSAR,molecular docking,ADME prediction and pharmacophore modeling studies for the search of novel antimalarial agent

In the present article, a dataset of 63 quinoxaline derivatives were taken for antimalarial activity and pharmacophore were developed. Atom based method was used to develop a three dimensional quantitative structure activity relationship (3D-QSAR) model. On comparison of all statistical parameters, model AHRRR23 was found to be the most effective and predictive QSAR model as it satisfied all statistical parameters of a good model. The model AHRRR23 showed an adequate R² value for the training set 0.9446, good predictive power with Q² of 0.6409, good F- value, low SD 0.1218 value and outstanding Pearson-R values and low RMSE 0.2779 values of the model. The docking studies also gives very good results with good RMSD values. 3D QSAR, docking and ADME studies exhibits that the developed model could be employed as a potential lead for further study as antimalarial drug.     

Combined 3D-QSAR modeling and molecular docking study on indolinone derivatives as inhibitors of 3-phosphoinositide-dependent protein kinase-1

3-Phosphoinositide-dependent protein kinase-1 (PDK1) is a promising target for developing novel anticancer drugs. In order to understand the structure-activity correlation of indolinone-based PDK1 inhibitors, we have carried out a combined molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling study. The study has resulted in two types of satisfactory 3D-QSAR models, including the CoMFA model (r(2)=0.907; q(2)=0.737) and CoMSIA model (r(2)=0.991; q(2)=0.824), for predicting the biological activity of new compounds. The detailed microscopic structures of PDK1 binding with inhibitors have been studied by molecular docking. We have also developed docking-based 3D-QSAR models (CoMFA with q(2)=0.729; CoMSIA with q(2)=0.79). The contour maps obtained from the 3D-QSAR models in combination with the docked binding structures help to better interpret the structure-activity relationship. All of the structural insights obtained from both the 3D-QSAR contour maps and molecular docking are consistent with the available experimental activity data. This is the first report on 3D-QSAR modeling of PDK1 inhibitors. The satisfactory results strongly suggest that the developed 3D-QSAR models and the obtained PDK1-inhibitor binding structures are reasonable for the prediction of the activity of new inhibitors and in future drug design.