Ul-Haq (2020): Identification of chymotrypsin-like protease inhibitors of SARS-CoV-2 via integrated computational approach, Journal of Biomolecular Structure and Dynamics, ABSTRACT Recently, the world has witnessed outbreak of a novel Coronavirus (SARS-CoV-2), the virus which initially emerged in Wuhan, China has now made its way to a large part of the world, resulting in a public emergency of international concern. The functional importance of Chymotrypsin-like protease (3CL pro ) in viral replication and maturation turns it into an attractive target for the development of effective antiviral drugs against SARS and other coronaviruses. At present, there is no standard drug regime nor any vaccine available against the infection. The rapid development and identification of efficient interventions against SARS-CoV-2 remains a major challenge. Based on the available knowledge of closely related coronavirus and their safety profiles, repurposing of existing antiviral drugs and screening of available databases is considered a near term strategic and economic way to contain the SARS-CoV-2 pandemic. Herein, we applied computational drug design methods to identify Chymotrypsin-like protease inhibitors from FDA approved antiviral drugs and our in-house database of natural and drug-like compounds of synthetic origin. As a result three FDA approved drugs (Remdesivir, Saquinavir and Darunavir) and two natural compounds (. flavone and coumarine derivatives) were identified as promising hits. Further, MD simulation and binding free energy calculations were performed to evaluate the dynamic behavior, stability of protein-ligand contact, and binding affinity of the hit compounds. Our results indicate that the identified compounds can inhibit the function of Chymotrypsin-like protease (3CL pro ) of Coronavirus. Considering the severity of the spread of coronavirus, the current study is in-line with the concept of finding the new inhibitors against the vital pathway of the corona virus to expedite the process of drug discovery.

Tumor Necrosis Factor Alpha (TNF-α) is a pleiotropic pro-inflammatory cytokine. It act as central biological regulator in critical immune functions, but its dysregulation has been linked with a number of diseases. Inhibition of TNF-α has considerable therapeutic potential for diseases such as cancer, diabetes, and especially autoimmune diseases. Despite the fact that many small molecule inhibitors have been identified against TNF-α, no orally active drug has been reported yet which demand an urgent need of a small molecule drug against TNF-α. This study focuses on the development of ligand-based selective pharmacophore model to perform virtual screening of plant origin natural product database for the identification of potential inhibitors against TNF-α. The resultant hits, identified as actives were evaluated by molecular docking studies to get insight into their potential binding interaction with the target protein. Based on pharmacophore matching, interacting residues, docking score, more affinity towards TNF-α with diverse scaffolds five compounds were selected for in vitro activity study. Experimental validation led to the identification of three chemically diverse potential compounds with the IC50 32.5 ± 4.5 µM, 6.5 ± 0.8 µM and 27.4 ± 1.7 µM, respectively.

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