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In 2019–2020, the novel “severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)” had emerged as the biggest challenge for humanity, causing “coronavirus disease 19 (COVID-19)”. Scientists around the world have been putting continuous efforts to unfold potential inhibitors of SARS-CoV-2. We have performed computational studies that help us to identify cyanobacterial photoprotective compounds as potential inhibitors against SARS-CoV-2 druggable target human angiotensin-converting enzyme (ACE2), which plays a vital role in the attachment and entry of the virus into the cell. Blocking the receptor-binding domain of ACE2 can prevent the access of the virus into the compartment. A molecular docking study was performed between photoprotective compounds mycosporine-like amino acids, scytonemins and ACE2 protein using AutoDock tools. Among sixteen molecularly docked metabolites, seven compounds were selected with binding energy < 6.8 kcal/mol. Afterwards, drug-likeness and toxicity of the top candidate were predicted using Swiss ADME and Pro Tox-II online servers. All top hits show desirable drug-likeness properties, but toxicity pattern analysis discloses the toxic effect of scytonemin and its derivatives, resulting in the elimination from the screening pipeline. Further molecular interaction study of the rest two ligands, mycosporine–glycine–valine and shinorine with ACE2 was performed using PyMol, Biovia Discovery studio and LigPlot+. Lastly biological activity of both the ligands was predicted by using the PASS online server. Combining the docking score and other studied properties, we believe that mycosporine–glycine–valine and shinorine have potential to be potent inhibitors of ACE2 and can be explored further to use against COVID-19.

The group of antigen 85 proteins of Mycobacterium tuberculosis is responsible for converting trehalose monomycolate to trehalose dimycolate, which contributes to cell wall stability. Here, we have used a serial enrichment approach to identify new potential inhibitors by searching the libraries of compounds using both 2D atom pair descriptors and binary fingerprints followed by molecular docking. Three different docking softwares AutoDock, GOLD, and LigandFit were used for docking calculations. In addition, we applied the criteria of selecting compounds with binding efficiency close to the starting known inhibitor and showing potential to form hydrogen bonds with the active site amino acid residues. The starting inhibitor was ethyl-3-phenoxybenzyl-butylphosphonate, which had IC(50) value of 2.0 μM in mycolyltransferase inhibition assay. Our search from more than 34 million compounds from public libraries yielded 49 compounds. Subsequently, selection was restricted to compounds conforming to the Lipinski rule of five and exhibiting hydrogen bonding to any of the amino acid residues in the active site pocket of all three proteins of antigen 85A, 85B, and 85C. Finally, we selected those ligands which were ranked top in the table with other known decoys in all the docking results. The compound NIH415032 from tuberculosis antimicrobial acquisition and coordinating facility was further examined using molecular dynamics simulations for 10 ns. These results showed that the binding is stable, although some of the hydrogen bond atom pairs varied through the course of simulation. The NIH415032 has antitubercular properties with IC(90) at 20 μg/ml (53.023 μM). These results will be helpful to the medicinal chemists for developing new antitubercular molecules for testing.

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