Tailored-pharmacophore model to enhance virtual screening and drug discovery: a case study on the identification of potential inhibitors against drug-resistant Mycobacterium tuberculosis (3R)-hydroxyacyl-ACP dehydratases

Aim: Virtual screening (VS) is powerful tool in discovering molecular inhibitors that are most likely to bind to drug targets of interest. Herein, we introduce a novel VS approach, so-called ‘tailored-pharmacophore’, in order to explore inhibitors that overcome drug resistance. Methodology & results: The emergence and spread of drug resistance strains of tuberculosis is one of the most critical issues in healthcare. A tailored-pharmacophore approach was found promising to identify in silico predicted hit with better binding affinities in case of the resistance mutations in MtbHadAB as compared with thiacetazone, a prodrug used in the clinical treatment of tuberculosis. Conclusion: This approach can potentially be enforced for the discovery and design of drugs against a wide range of resistance targets.

Zika virus NS5 protein potential inhibitors: an enhanced in silico approach in drug discovery

The re-emerging Zika virus (ZIKV) is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus has already been linked to irreversible chronic central nervous system conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of ZIKV Methyltransferase and RNA dependent RNA polymerase. This in silico 'per-residue energy decomposition pharmacophore' virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.

Hybrid Receptor-Bound/MM-GBSA-Per-residue Energy-Based Pharmacophore Modelling: Enhanced Approach for Identification of Selective LTA4H Inhibitors as Potential Anti-inflammatory Drugs

Leukotriene A₄ hydrolase has been identified as an enzyme with dual anti- and pro-inflammatory role, thus, the conversion of leukotriene to leukotriene B₄ in the initiation stage of inflammation and the removal of the chemotactic Pro-Gly-Pro tripeptide. These findings make leukotriene A₄ hydrolase an attractive drug target: suggesting an innovative approach towards the identification and design of novel class of compounds that can selectively inhibit leukotriene B₄ synthesis while sparing the aminopeptidase activity. Previous inhibitors block the dual activity of the enzyme. Recently, a small lead molecule inhibitor denoted as ARM1 has been identified to block the hydrolase activity of leukotriene A₄ hydrolase whilst sparing the aminopeptidase activity. In this study, a hybrid receptor-bound/MM-GBSA-per-residue energy based pharmacophore modeling approach was implemented to identify potential selective hydrolase inhibitors of leukotriene A₄ hydrolase. In this approach, active site residues that favorably contributed to the binding of the bound conformation of ARM1 were derived from MD ensembles and MM/GBSA thermodynamic calculations. These residues were then mapped to key pharmacophore features of ARM1. The generated pharmacophore model was used to search the ZINC database for 3D structures that match the pharmacophore. Five new compounds have been identified and proposed as potential epoxide hydrolase selective inhibitors of leukotriene A₄ hydrolase. Molecular docking and MM/GBSA analyses revealed that, these top five lead-like compounds ZINC00142747, ZINC94260794, ZINC01382396, ZINC02508448, and ZINC53994447 showed better binding affinities to the hydrolase active site pocket compared to ARM1. Per-residue energy decomposition analysis revealed that amino acid residues Phe314, Tyr378, Pro382, Trp311, Val367, and Ala377 are key residues critical in the selective inhibition of these hits. Information highlighted in this study may guide the the design the next generation of novel and potent epoxide hydrolase selective inhibitors of leukotriene A₄ hydrolase.

Recent advancements in the development of anti-tuberculosis drugs

Modern chemotherapy has significantly improved patient outcomes against drug-sensitive tuberculosis. However, the rapid emergence of drug-resistant tuberculosis, together with the bacterium's ability to persist and remain latent present a major public health challenge. To overcome this problem, research into novel anti-tuberculosis targets and drug candidates is thus of paramount importance. This review article provides an overview of tuberculosis highlighting the recent advances and tools that are employed in the field of anti-tuberculosis drug discovery. The predominant focus is on anti-tuberculosis agents that are currently in the pipeline, i.e. clinical trials.

The impact of active site mutations of South African HIV PR on drug resistance: Insight from molecular dynamics simulations, binding free energy and per-residue footprints

Molecular dynamics simulations and binding free energy calculations were used to provide an understanding of the impact of active site drug-resistant mutations of the South African HIV protease subtype C (C-SA HIV PR), V82A and V82F/I84V on drug resistance. Unique per-residue interaction energy 'footprints' were developed to map the overall drug-binding profiles for the wild type and mutants. Results confirmed that these mutations altered the overall binding landscape of the amino acid residues not only in the active site region but also in the flaps as well. Four FDA-approved drugs were investigated in this study; these include ritonavir (RTV), saquinavir (SQV), indinavir (IDV), and nelfinavir (NFV). Computational results compared against experimental findings were found to be complementary. Against the V82F/I84V variant, saquinavir, indinavir, and nelfinavir lose remarkable entropic contributions relative to both wild-type and V82A C-SA HIV PRs. The per-residue energy 'footprints' and the analysis of ligand-receptor interactions for the drug complexes with the wild type and mutants have also highlighted the nature of drug interactions. The data presented in this study will prove useful in the design of more potent inhibitors effective against drug-resistant HIV strains.

Molecular modeling studies of dihydro-alkyloxy-benzyl-oxopyrimidines (DABOs) as non-nucleoside inhibitors of HIV-1 reverse transcriptase using 3D-QSAR, Topomer CoMFA and molecular docking simulations

The human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) is generally regarded as a target for the treatment of acquired immune deficiency syndrome (AIDS).

Integrated computational tools for identification of CCR5 antagonists as potential HIV-1 entry inhibitors: homology modeling, virtual screening, molecular dynamics simulations and 3D QSAR analysis

Using integrated in-silico computational techniques, including homology modeling, structure-based and pharmacophore-based virtual screening, molecular dynamic simulations, per-residue energy decomposition analysis and atom-based 3D-QSAR analysis, we proposed ten novel compounds as potential CCR5-dependent HIV-1 entry inhibitors. Via validated docking calculations, binding free energies revealed that novel leads demonstrated better binding affinities with CCR5 compared to maraviroc, an FDA-approved HIV-1 entry inhibitor and in clinical use. Per-residue interaction energy decomposition analysis on the averaged MD structure showed that hydrophobic active residues Trp86, Tyr89 and Tyr108 contributed the most to inhibitor binding. The validated 3D-QSAR model showed a high cross-validated r_cv² value of 0.84 using three principal components and non-cross-validated r² value of 0.941. It was also revealed that almost all compounds in the test set and training set yielded a good predicted value. Information gained from this study could shed light on the activity of a new series of lead compounds as potential HIV entry inhibitors and serve as a powerful tool in the drug design and development machinery.