Identification of potential HIV-1 integrase strand transfer inhibitors: In silico virtual screening and QM/MM docking studies

HIV-1 integrase (IN) is a retroviral enzyme that catalyses integration of the reverse-transcribed viral DNA into the host genome, which is necessary for efficient viral replication. In this study, we have performed an in silico virtual screening for the identification of potential HIV-1 IN strand transfer (ST) inhibitors. Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to 3-Hydroxypyrimidine-2,4-diones. Based on the ligand-based pharmacophore model, we obtained a five-point pharmacophore with two hydrogen bond acceptors (A), one hydrogen bond donor (D), one hydrophobic group (H) and one aromatic ring (R) as pharmacophoric features. The pharmacophore hypothesis AADHR was used as a 3D query in a sequential virtual screening study to filter small molecule databases Maybridge, ChemBridge and Asinex. Hits matching with pharmacophore hypothesis AADHR were retrieved and passed progressively through Lipinski’s rule of five filtering, molecular docking and hierarchical clustering. The five compounds with best hits with novel and diverse chemotypes were subjected to QM/MM docking, which showed improved docking accuracy. We further performed molecular dynamics simulation and found three compounds that form stable interactions with key residues. These compounds could be used as a leads for further drug development and rational design of HIV-1 IN inhibitors.     

Theory of docking scores and its application to a customizable scoring function

In general, the docking scoring tends to have a size dependence related to the ranking of compounds. In this paper, we describe a novel method of parameter optimization for docking scores which reduce the size dependence and can efficiently discriminate active compounds from chemical databases. This method is based on a simplified theoretical model of docking scores which enables us to utilize large amounts of data of known active and inactive compounds for a particular target without requiring large computational resources or a complicated procedure. This method is useful for making scoring functions for the identification of novel scaffolds using the knowledge of active compounds for a particular target or a customized scoring function for an interesting family of drug targets.     

Pharmacophore modelling,molecular docking and virtual screening for EGFR (HER 1) tyrosine kinase inhibitors

A pharmacophore model has been developed using diverse classes of epidermal growth factor receptor (EGFR) tyrosine kinase (TK) inhibitors useful in the treatment of human tumours. Among the top 10 generated hypotheses, the second hypothesis, with one hydrogen bond acceptor, one ring aromatic and three hydrophobic features, was found to be the best on the basis of Cat Scramble validation as well as test set prediction (r _training?=?0.89, r _test?=?0.82). The model also maps well to the external test set molecules as well as clinically active molecules and corroborates the docking studies. Finally, 10 hits were identified as potential leads after virtual screening of ZINC database for EGFR TK inhibition. The study may facilitate the designing and discovery of novel EGFR TK inhibitors.     

Analysis of Ah receptor binding affinities of polybrominated diphenyl ethers via in silico molecular docking and 3D-QSAR

Polybrominated diphenyl ethers (PBDEs) have become ubiquitous contaminations due to their use as flame retardants. The structural similarity of PBDE to some dioxin-like compounds suggested that they may share similar toxicological effects: they might activate the aryl hydrocarbon receptor (AhR) signal transduction pathway and thus might have adverse effects on wildlife and humans. In this study, in silico computational workflow combining molecular docking and three-dimensional quantitative structure–activity relationship (3D-QSAR) was performed to investigate the binding interactions between PBDEs and AhR and the structural features affecting the AhR binding affinity of PBDE. The molecular docking showed that hydrogen-bond and hydrophobic interactions were the major driving forces for the binding of ligands to AhR, and several key amino acid residues were also identified. The CoMSIA model was developed from the conformations obtained from molecular docking and exhibited satisfactory results as q ² of 0.605 and r ² of 0.996. Furthermore, the derived model had good robustness and statistical significance in both internal and external validations. The 3D contour maps generated from CoMSIA provided important structural features influence the binding affinity. The obtained results were beneficial to better understand the toxicological mechanism of PBDEs.     

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.     

Asymmetric Synthesis, Antifungal Activity and Molecular Modeling of Iodiconazole Isomers

Iodiconazole is a novel antifungal agent that was developed in its racemic form. In order to investigate the ef- fects of the chiral center on the antifungal activity, R- and S-isomers of iodiconazole were prepared on the basis of the asymmetric Sharpless epoxidation. （S）-Iodiconazole was proved to have better antifungal activity than the （R）- isomer. The binding modes of the two isomers with lanosterol 14~z-demethylase were clarified by molecular dock- ing.     

Triazole and Benzotriazole Derivatives as Novel Inhibitors for p90 Ribosomal S6 Protein Kinase 2： Synthesis, Molecular Docking and SAR Analysis

A series of triazole and benzotriazole derivatives as novel p90 ribosomal S6 protein kinase 2 （RSK2） inhibitors were designed and synthesized. The in vitro activities against RSK2 were evaluated, and among 14 compounds, compounds 5, 6, 11, 12, 13 and 14 exhibited enzyme IC50 values of 8.91, 2.86, 3.19, 3.05, 4.49 and 2.09 μmol/L re- spectively. The proposed binding modes were simulated using molecular docking method, and the docking results coupled with the stmcture-activi1：y relationship （SAR） analysis indicated that all these active compounds bound to the RSK2 ATP binding site at NTKD, and the electron-donating groups on the 4-position of phenyl were the deter- minant point for the inhibitory activity.     

Synthesis,ABTS-Radical Scavenging Activity,and Antiproliferative and Molecular Docking Studies of Novel Pyrrolo[1,2-a]quinoline Derivatives

A new 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS)-radical scavenging and antiproliferative agents of pyrrolo[1,2-a]quinoline derivatives have been synthesized. An efficient method for the synthesis of 14 novel diversified pyrrolo[1,2-a]quinoline derivatives has been described using 4-(1,3-dioxolan-2-yl)quinoline and different phenacyl bromides in acetone and followed by reacting with different acetylenes in dimethylformamide/K₂CO₃. The structure of the newly synthesized compounds was determined by infrared, ¹H NMR, ¹³C NMR, mass spectrometry, and elemental analysis. The in vitro antioxidant activity revealed that among all the tested compounds 5n exhibited maximum scavenging activity with ABTS. Compound 5b has showed good antiproliferative activity as an inhibitor of epidermal growth factor receptor (EGFR) tyrosine kinase.     

FIPSDock: A new molecular docking technique driven by fully informed swarm optimization algorithm

The accurate prediction of protein–ligand binding is of great importance for rational drug design. We present herein a novel docking algorithm called as FIPSDock, which implements a variant of the Fully Informed Particle Swarm (FIPS) optimization method and adopts the newly developed energy function of AutoDock 4.20 suite for solving flexible protein–ligand docking problems. The search ability and docking accuracy of FIPSDock were first evaluated by multiple cognate docking experiments. In a benchmarking test for 77 protein/ligand complex structures derived from GOLD benchmark set, FIPSDock has obtained a successful predicting rate of 93.5% and outperformed a few docking programs including particle swarm optimization (PSO)@AutoDock, SODOCK, AutoDock, DOCK, Glide, GOLD, FlexX, Surflex, and MolDock. More importantly, FIPSDock was evaluated against PSO@AutoDock, SODOCK, and AutoDock 4.20 suite by cross‐docking experiments of 74 protein–ligand complexes among eight protein targets (CDK2, ESR1, F2, MAPK14, MMP8, MMP13, PDE4B, and PDE5A) derived from Sutherland‐crossdock‐set. Remarkably, FIPSDock is superior to PSO@AutoDock, SODOCK, and AutoDock in seven out of eight cross‐docking experiments. The results reveal that FIPS algorithm might be more suitable than the conventional genetic algorithm‐based algorithms in dealing with highly flexible docking problems. © 2012 Wiley Periodicals, Inc.     

VinaMPI: Facilitating multiple receptor high‐throughput virtual docking on high‐performance computers

The program VinaMPI has been developed to enable massively large virtual drug screens on leadership‐class computing resources, using a large number of cores to decrease the time‐to‐completion of the screen. VinaMPI is a massively parallel Message Passing Interface (MPI) program based on the multithreaded virtual docking program AutodockVina, and is used to distribute tasks while multithreading is used to speed‐up individual docking tasks. VinaMPI uses a distribution scheme in which tasks are evenly distributed to the workers based on the complexity of each task, as defined by the number of rotatable bonds in each chemical compound investigated. VinaMPI efficiently handles multiple proteins in a ligand screen, allowing for high‐throughput inverse docking that presents new opportunities for improving the efficiency of the drug discovery pipeline. VinaMPI successfully ran on 84,672 cores with a continual decrease in job completion time with increasing core count. The ratio of the number of tasks in a screening to the number of workers should be at least around 100 in order to have a good load balance and an optimal job completion time. The code is freely available and downloadable. Instructions for downloading and using the code are provided in the Supporting Information. © 2013 Wiley Periodicals, Inc.