In Silico Evaluation of Human Cathelicidin LL-37 as a Novel Therapeutic Inhibitor of Panton-Valentine Leukocidin Toxin of Methicillin-Resistant Staphylococcus aureus.

Incidence of drug resistance in clinical isolates of methicillin-resistant Staphylococcus aureus (MRSA) is attributed to its diverse repertoire of virulence factors. Of these virulence determinants, Panton-Valentine Leukocidin (PVL) has been experimentally validated as a prospective drug target due to its conspicuous and comprehensive role in nosocomial infections. This study encompassed an in silico approach to elucidate the antimicrobial potentiality of human cathelicidin LL-37 against PVL toxin of MRSA. Molecular docking studies of LL-37 and its segments with the PVL toxin subunits LukS and LukF were carried out using PatchDock server and the results were refined using FireDock server. The paramount ligand-receptor combination was selected and analyzed based on diverse parametric attributes and compared with the commercial inhibitors of PVL viz. Andrimid, Beclobrate, Beta-sitosterol, Diathymosulfone, and Probucol to determine the most potent inhibitor among them. Our results elucidated that the interaction of LL-37 with the LukS subunit of PVL toxin (minimum global energy of -61.82 kcal/mol) depicted 34 molecular interactions, while the commercial PVL inhibitors depicted fewer and insubstantial interactions. SWISS-ADME (Absorption, Distribution, Metabolism, and Excretion) and ToxinPred analysis of LL-37 further corroborated its null potency of toxicity in systemic milieu. The results obtained may credit this study as basis for the development of LL-37 as a potential inhibitor against virulent MRSA toxins, thereby exalting the treatment regimes for nosocomial infections in health care facilities worldwide.

Computational drug re-purposing targeting the spike glycoprotein of SARS-CoV-2 as an effective strategy to neutralize COVID-19.

COVID-19 has intensified into a global pandemic with over a million deaths worldwide. Experimental research analyses have been implemented and executed with the sole rationale to counteract SARS-CoV-2, which has initiated potent therapeutic strategy development in coherence with computational biology validation focusing on the characterized viral drug targets signified by proteomic and genomic data. Spike glycoprotein is one of such potential drug target that promotes viral attachment to the host cellular membrane by binding to its receptor ACE-2 via its Receptor-Binding Domain (RBD). Multiple Sequence alignment and relative phylogenetic analysis revealed significant sequential disparities of SARS-CoV-2 as compared to previously encountered SARS-CoV and MERS-CoV strains. We implemented a drug re-purposing approach wherein the inhibitory efficacy of a cluster of thirty known drug candidates comprising of antivirals, antibiotics and phytochemicals (selection contingent on their present developmental status in underway clinical trials) was elucidated by subjecting them to molecular docking analyses against the spike protein RBD model (developed using homology modelling and validated using SAVES server 5.0) and the composite trimeric structures of spike glycoprotein of SARS-CoV-2. Our results indicated that Camostat, Favipiravir, Tenofovir, Raltegravir and Stavudine showed significant interactions with spike RBD of SARS-CoV-2. Proficient bioavailability coupled with no predicted in silico toxicity rendered them as prospective alternatives for designing and development of novel combinatorial therapy formulations for improving existing treatment regimes to combat COVID-19.