TY - JOUR
T1 - In silico study to evaluate the antiviral activity of novel structures against 3c-like protease of novel coronavirus (Covid-19) and sars-cov
AU - Chunduru, Kiran
AU - Sankhe, Runali
AU - Begum, Farmiza
AU - Sodum, Nalini
AU - Kumar, Nitesh
AU - Kishore, Anoop
AU - Shenoy, Rekha R.
AU - Rao, C. Mallikarjuna
AU - Saravu, Kavitha
N1 - Funding Information:
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors are thankful to Manipal ? Schr?dinger Cen-tre for Molecular Simulations, Manipal College of Pharmaceutical Sciences, and Manipal Academy of Higher Education for providing necessary support and research facilities to carry out the research work. The authors are thankful to Alex Zhavoronkov from Insilico Medicine, Hong Kong, China, who is one of the authors of research paper citation ?Zhavo-ronkov, Alex; Aladinskiy, Vladimir; Zhebrak, Alexander; Zagribelnyy, Bogdan; Terentiev, Victor; Bezrukov, Dmitry S.; et al. (2020): Potential COVID-2019 3C-like Protease Inhibitors Designed Using Generative Deep Learning Ap-proaches. ChemRxiv. Preprint. https://doi.org/10.26434/chemrxiv.11829102.v2?. Authors also acknowledge BioRender Science Suite Inc.
Publisher Copyright:
© 2021 Bentham Science Publishers.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021
Y1 - 2021
N2 - Background: Globally, over 4.3 million laboratory confirmed cases of COVID-19 have been reported from over 105 countries. No FDA approved antiviral is available for the treatment of this infection. Zhavoronkov et al., with their generative chemistry pipeline, have generated structures that can be potential novel drug-like inhibitors for COVID-19, provided they are validated. 3C–like protease (3CLP) is a homodimeric cysteine protease that is present in coronaviruses. Interestingly, 3CLP is 96.1% structurally similar between SARS-CoV and SARS-CoV-2. Objective: To evaluate interaction of generated structures with 3CLP of SARS-CoV (RCSB PDB ID: 4MDS). Methods: Crystal structure of human SARS-CoV with a non-covalent inhibitor with resolution: 1.598 Å was obtained and molecular docking was performed to evaluate the interaction with generated structures. The MM-GBSA and IFD-SP were performed to narrow down to the structures with better binding energy and IFD score. The ADME analysis was performed on top 5 hits and further MD simulation was employed for top 2 hits. Results: In XP docking, IFD-SP and molecular dynamic simulation studies, the top 2 hits 32 and 61 showed interaction with key amino acid residue GLU166. Structure 61, also showed interaction with HIS164. These interactions of generated structure 32 and 61, with GLU166 and HIS164, indicate the binding of the selected drug within the close proximity of 3CLP. In the MD simulation, the protein– ligand complex of 4MDS and structure 61 was found to be more stable for 10ns. Conclusion: These identified structures can be further assessed for their antiviral activity to combat SARS-CoV and COVID-19.
AB - Background: Globally, over 4.3 million laboratory confirmed cases of COVID-19 have been reported from over 105 countries. No FDA approved antiviral is available for the treatment of this infection. Zhavoronkov et al., with their generative chemistry pipeline, have generated structures that can be potential novel drug-like inhibitors for COVID-19, provided they are validated. 3C–like protease (3CLP) is a homodimeric cysteine protease that is present in coronaviruses. Interestingly, 3CLP is 96.1% structurally similar between SARS-CoV and SARS-CoV-2. Objective: To evaluate interaction of generated structures with 3CLP of SARS-CoV (RCSB PDB ID: 4MDS). Methods: Crystal structure of human SARS-CoV with a non-covalent inhibitor with resolution: 1.598 Å was obtained and molecular docking was performed to evaluate the interaction with generated structures. The MM-GBSA and IFD-SP were performed to narrow down to the structures with better binding energy and IFD score. The ADME analysis was performed on top 5 hits and further MD simulation was employed for top 2 hits. Results: In XP docking, IFD-SP and molecular dynamic simulation studies, the top 2 hits 32 and 61 showed interaction with key amino acid residue GLU166. Structure 61, also showed interaction with HIS164. These interactions of generated structure 32 and 61, with GLU166 and HIS164, indicate the binding of the selected drug within the close proximity of 3CLP. In the MD simulation, the protein– ligand complex of 4MDS and structure 61 was found to be more stable for 10ns. Conclusion: These identified structures can be further assessed for their antiviral activity to combat SARS-CoV and COVID-19.
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U2 - 10.2174/1573396316999200727125522
DO - 10.2174/1573396316999200727125522
M3 - Article
C2 - 32720605
AN - SCOPUS:85101621503
SN - 1573-4064
VL - 17
SP - 380
EP - 395
JO - Medicinal Chemistry
JF - Medicinal Chemistry
IS - 4
ER -