An in-silico approach to identify the potential hot spots in SARS-CoV-2 spike RBD to block the interaction with ACE2 receptor

Abstract

A novel acute viral pneumonia induced by SARS-CoV-2 exploded at the end of 2019, causing a severe medical and economic crisis. For developing specific pharmacotherapy against SARS-CoV-2, an in silico virtual screening was developed for the available in-house molecules. The conserved domain analysis was performed to identify the highly conserved and exposed amino acid regions in the SARS-CoV-2-S RBD sites. The Protein-Protein interaction analyses demonstrated the higher affinity between the SARS-CoV-2-S and ACE2 due to varieties of significant interactions between them. The computational alanine scanning mutation study has recognized the highly stabilized amino acids in the SARS-CoV-2-S RBD/ACE2 complex. The cumulative sequence investigations have inferred that Lys417, Phe486, Asn487, Tyr489, and Gln493 are perhaps the iconic target amino acids to develop a drug molecule or vaccine against SARS-CoV-2 infection. Most of the selected compounds include luteolin, zhebeirine, 3-dehydroverticine, embelin, andrographolide, ophiopogonin D, crocin-1, sprengerinin A, B, C, peimine, etc. were exhibited distinguish drug actions through the strong hydrogen bonding with the hot spots of the RBD. Besides, the 100 ns molecular dynamics simulation and free energy binding analysis showed the significant efficacy of luteolin to inhibit the infection of SARS-CoV-2.

Highlights:

• Highly conserved and exposed amino acids in the SARS-CoV-2-S-RBD sites has been identified

• Computational alanine scanning mutation study has recognized the highly stabilized hot spots in the SARS-CoV-2-S RBD/ACE2 complex.

• Virtual screening has been executed to identify the drug actions in the RBD region

• Most of the selected natural products were involved in the distinctive strong interactions with hot spots of RBD to inhibit the infection of SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2-S RBD
• conserved domain
• alanine scanning
• natural compounds
• molecular docking
• MD simulation

Disclosure statement

The authors have declared no conflicts of interest.

Additional information

Funding

The authors gratefully acknowledge the financial support provided by the Postdoctoral fund of Zhejiang Province (zj2019142), China, to Dr. Antony Stalin. Also, the authors thank for the financial support through the Opening Project of Zhejiang Provincial Preponderant and Characteristic Subject of Key University (Traditional Chinese Pharmacology), Zhejiang Chinese Medical University (No. ZYAOXYB2019008). Prof. Dong-Qing Wei is supported by grants from the National Science Foundation of China (Grant No. 32070662, 61832019, 32030063), The Key Research Area Grant 2016YFA0501703 of the Ministry of Science and Technology of China, the Science and Technology Commission of Shanghai Municipality (Grant No.: 19430750600), as well as SJTU JiRLMDS Joint Research Fund and Joint Research Funds for Medical and Engineering and Scientific Research at Shanghai Jiao Tong University (YG2021ZD02). The computations were partially performed at the Pengcheng Lab and the Center for High-Performance Computing, Shanghai Jiao Tong University.