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Struct Chem ; : 1-15, 2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1942564


Coronavirus disease 2019 (COVID-19) has become a major challenge affecting almost every corner of the world, with more than five million deaths worldwide. Despite several efforts, no drug or vaccine has shown the potential to check the ever-mutating SARS-COV-2. The emergence of novel variants is a major concern increasing the need for the discovery of novel therapeutics for the management of this pandemic. Out of several potential drug targets such as S protein, human ACE2, TMPRSS2 (transmembrane protease serine 2), 3CLpro, RdRp, and PLpro (papain-like protease), RNA-dependent RNA polymerase (RdRP) is a vital enzyme for viral RNA replication in the mammalian host cell and is one of the legitimate targets for the development of therapeutics against this disease. In this study, we have performed structure-based virtual screening to identify potential hit compounds against RdRp using molecular docking of a commercially available small molecule library of structurally diverse and drug-like molecules. Since non-optimal ADME properties create hurdles in the clinical development of drugs, we performed detailed in silico ADMET prediction to facilitate the selection of compounds for further studies. The results from the ADMET study indicated that most of the hit compounds had optimal properties. Moreover, to explore the conformational dynamics of protein-ligand interaction, we have performed an atomistic molecular dynamics simulation which indicated a stable interaction throughout the simulation period. We believe that the current findings may assist in the discovery of drug candidates against SARS-CoV-2.

J Biomol Struct Dyn ; 40(8): 3609-3625, 2022 05.
Article in English | MEDLINE | ID: covidwho-939480


COVID-19 pandemic has created a healthcare crisis across the world and has put human life under life-threatening circumstances. The recent discovery of the crystallized structure of the main protease (Mpro) from SARS-CoV-2 has provided an opportunity for utilizing computational tools as an effective method for drug discovery. Targeting viral replication has remained an effective strategy for drug development. Mpro of SARS-COV-2 is the key protein in viral replication as it is involved in the processing of polyproteins to various structural and nonstructural proteins. Thus, Mpro represents a key target for the inhibition of viral replication specifically for SARS-CoV-2. We have used a virtual screening strategy by targeting Mpro against a library of commercially available compounds to identify potential inhibitors. After initial identification of hits by molecular docking-based virtual screening further MM/GBSA, predictive ADME analysis, and molecular dynamics simulation were performed. The virtual screening resulted in the identification of twenty-five top scoring structurally diverse hits that have free energy of binding (ΔG) values in the range of -26-06 (for compound AO-854/10413043) to -59.81 Kcal/mol (for compound 329/06315047). Moreover, the top-scoring hits have favorable AMDE properties as calculated using in silico algorithms. Additionally, the molecular dynamics simulation revealed the stable nature of protein-ligand interaction and provided information about the amino acid residues involved in binding. Overall, this study led to the identification of potential SARS-CoV-2 Mpro hit compounds with favorable pharmacokinetic properties. We believe that the outcome of this study can help to develop novel Mpro inhibitors to tackle this pandemic.Communicated by Ramaswamy H. Sarma.

COVID-19 , Molecular Dynamics Simulation , COVID-19/drug therapy , Coronavirus 3C Proteases , Humans , Molecular Docking Simulation , Pandemics , Protease Inhibitors/chemistry , Protease Inhibitors/pharmacology , SARS-CoV-2