Structure-Based Virtual Screening and Molecular Dynamics Simulation to Identify Potential SARS-CoV-2 Spike Receptor Inhibitors from Natural Compound Database.

The outbreak of respiratory disease, COVID-19 caused by SARS-CoV-2 has now been spread globally and the number of new infections is rising every moment. There are no specific medications that are currently available to combat the disease. The spike receptor of SARS-CoV-2 facilitates the viral entry into a host cell and initiation of infection. Targeting the viral entry at the initial stage has a better advantage than inhibiting it in later stages of the viral life cycle. This study deals with identification of the potential natural molecule or its derivatives from MolPort Databank as SARS-CoV-2 spike receptor inhibitors using structure-based virtual screening followed by molecular dynamics simulation. On the basis of ADME properties, docking score, MMGBSAbinding energy, 150 ns molecular docking studies, and final molecular dynamics analysis, two natural compounds - 3 (MolPort-002-535-004) docking score -9.10 kcal mol-1 and 4 (MolPort-005-910-183) docking score -8.5 kcal mol-1, are selected as potential in-silico spike receptor inhibitors. Both hits are commercially available and can be further used for in-vitro and in-vivo studies. Findings of this study can facilitate rational drug design against SARS-CoV-2 spike receptor.

Insilico studies on anthrax lethal factor inhibitors: pharmacophore modeling and virtual screening approaches towards designing of novel inhibitors for a killer.

Bacillus anthracis is a causative organism of anthrax. The main reason to use anthrax as a bioweapon is the combination of the spore's durability and the lethal toxaemia of the vegetative stage. In anthrax infection, lethal factor (LF) is playing crucial role in causing cell death, by inhibiting pathways that rely on this kinase family. The combination of vaccine and antibiotics is preferred as an effective treatment for this target. Till date, no small molecule inhibitor is identified as a drug on the target. In this study, we have performed pharmacophore modeling and docking studies to identify a novel small molecule inhibitor to target the Anthrax LF. The best pharmacophore model is used to screen approximately 2M drug-like small molecule database and yielded 2543 hits. Docking studies of the pharmacophore hits on to the active site of Anthrax LF resulted 120 structurally diverse hits. Out of 120 hits, based on synthetic feasibility, 17 hits are selected for further synthesis and pharmacological screening. In due course, we will publish the updated results.