Exploration of the structural requirements of HIV-protease inhibitors using pharmacophore, virtual screening and molecular docking approaches for lead identification

A molecular dynamics perspective into estrogen receptor inhibition by selective flavonoids as alternative therapeutic options

Zearalenone is an estrogenic mycotoxin which is a common food contaminant and has been implicated in increasing the incidence of carcinogenesis and other reproductive health ailments through the estrogen receptor alpha (ERα) pathway. Competitive ERα blockers such as 4-Hydroxytamoxifen (OHT), are synthetic FDA approved drugs which, albeit being an effective anticancer agent, induces life altering side effects. For this reason, there is an increased interest in the use of naturally occurring medicinal plant products such as flavonoids. This study aimed to identity flavonoid ERα inhibitors and provide insights into the mechanism of inhibition using computational techniques. The Molecular Mechanics/Generalized Born Surface Area calculations revealed that quercetrin, hesperidin, epigallocatechin 3-gallate and kaempferol 7-O-glucoside out of 14 flavonoids had higher binding affinity for ERα than OHT. The structural analysis revealed that the binding of the compounds to the receptor lead to dynamic alterations, which induced conformational shift in the structure and orientation of the receptor resulting in stabilised, compact and low energy systems. The results of this study provide imperative information that supports the use of flavonoids in the inhibition of ERα to prevent or ameliorate the consequential adverse effects associated with zearalenone exposure.Communicated by Ramaswamy H. Sarma.

Matairesinol, an active constituent of HC9 polyherbal formulation, exhibits HDAC8 inhibitory and anticancer activity

Histone deacetylase 8 (HDAC8) has emerged as a promising drug target for cancer therapeutics development. HDAC8 has been reported to regulate cancer cell proliferation, invasion and promote metastasis through modulation of cell cycle associated proteins. Of late, phytocompounds have been demonstrated to exhibit anticancer and anti-HDAC8 activity. Here, we have shown the HDAC8 inhibitory potential of an active phytocompound from HC9 (herbal composition-9), a polyherbal anticancer formulation based on the traditional Ayurvedic drug, Stanya Shodhan Kashaya. HC9 was recently reported to exhibit anticancer activity against breast cancer cells through induction of cell cycle arrest, decrease in migration and invasion as well as regulation of inflammation and chromatin modulators. In silico studies such as molecular docking, molecular dynamics (MD) simulation and binding free energy analyses showed greater binding energy values and interaction stability of MA with HDAC8 compared to other phytocompounds of HC9. Interestingly, in vitro validation confirmed the anti-HDAC8 activity of MA. Further, in vitro studies showed that MA significantly decreased the viability of breast and prostate cancer cell lines, thereby confirming its anticancer potential.

Structural refinement and prediction of potential CCR2 antagonists through validated multi-QSAR modeling studies

Chemokines trigger numerous inflammatory responses and modulate the immune system. The interaction between monocyte chemoattractant protein-1 and chemokine receptor 2 (CCR2) may be the cause of atherosclerosis, obesity, and insulin resistance. However, CCR2 is also implicated in other inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, asthma, and neuropathic pain. Therefore, there is a paramount importance of designing potent and selective CCR2 antagonists despite a number of drug candidates failed in clinical trials. In this article, 83 CCR2 antagonists by Jhonson and Jhonson Pharmaceuticals have been considered for robust validated multi-QSAR modeling studies to get an idea about the structural and pharmacophoric requirements for designing more potent CCR2 antagonists. All these QSAR models were validated and statistically reliable. Observations resulted from different modeling studies correlated and validated results of other ones. Finally, depending on these QSAR observations, some new molecules were proposed that may exhibit higher activity against CCR2.

Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents

A novel virtual screening approach is implemented herein, which is a further improvement of our previously published "target-bound pharmacophore modeling approach". The generated pharmacophore library is based only on highly contributing amino acid residues, instead of arbitrary pharmacophores, which are most commonly used in the conventional approaches in literature. Highly contributing amino acid residues were distinguished based on free binding energy contributions obtained from calculation from molecular dynamic (MD) simulations. To the best of our knowledge; this is the first attempt in the literature using such an approach; previous approaches have relied on the docking score to generate energy-based pharmacophore models. However, docking scores are reportedly unreliable. Thus, we present a model for a per-residue energy decomposition, constructed from MD simulation ensembles generating a more trustworthy pharmacophore model, which can be applied in drug discovery workflow. This work is aimed at introducing a more rational approach to the field of drug design, rather than comparing the validity of this approach against those previously reported. We recommend additional computational and experimental work to further validate this approach. This approach was used to screen for potential reverse transcriptase inhibitors using the pharmacophoric features of compound GSK952. The complex was subjected to docking, thereafter, MD simulation confirmed the stability of the system. Experimentally determined inhibitors with known HIV-reverse transcriptase inhibitory activity were used to validate the protocol. Two potential hits (ZINC46849657 and ZINC54359621) showed a significant potential with regard to free binding energy. Reported results obtained from this work confirm that this new approach is favorable in the future of the drug design industry.

Constructing an atomic-resolution model of human P2X7 receptor followed by pharmacophore modeling to identify potential inhibitors

The P2X purinoceptor 7 (P2X7R) is a trimeric ATP-activated ion channel gated by extracellular ATP. P2X7R has important role in numerous diseases including pain, neurodegeneration, and inflammatory diseases such as rheumatoid arthritis and osteoarthritis. In this prospective, the discovery of small-molecule inhibitors for P2X7R as a novel therapeutic target has received considerable attention in recent years. At first, 3D structure of P2X7R was built by using homology modeling (HM) and a 50ns molecular dynamics simulation (MDS). Ligand-based quantitative pharmacophore modeling methodology of P2X7R antagonists were developed based on training set of 49 compounds. The best four-feature pharmacophore model, includes two hydrophobic aromatic, one hydrophobic and one aromatic ring features, has the highest correlation coefficient (0.874), cost difference (368.677), low RMSD (2.876), as well as it shows a high goodness of fit and enrichment factor. Consequently, some hit compounds were introduced as final candidates by employing virtual screening and molecular docking procedure simultaneously. Among these compounds, six potential molecule were identified as potential virtual leads which, as such or upon further optimization, can be used to design novel P2X7R inhibitors.