Inhibition of multiple SARS-CoV-2 proteins by an antiviral biomolecule, seselin from Aegle marmelos deciphered using molecular docking analysis

Abstract

Our earlier experimental and computational report produced evidence on the antiviral nature of the compound seselin purified from the leaf extracts of Aegle marmelos against Bombyx mori Nuclear Polyhedrosis Virus (BmNPV). In the pandemic situation of COVID-19 caused by the SARS-COV-2 virus, an in silico effort to evaluate the potentiality of the seselin was made to test its efficacy against multiple targets of SARS-COV-2 such as spike protein S2, COVID-19 main protease and free enzyme of the SARS-CoV-2 (2019-nCoV) main protease. The ligand seselin showed the best interaction with receptors, spike protein S2, COVID-19 main protease and free enzyme of the SARS-CoV-2 (2019-nCoV) main protease with a binding energy of −6.3 kcal/mol, −6.9 kcal/mol and −6.7 kcal/mol, respectively. Docking analysis with three different receptors identified that all the computationally predicted lowest energy complexes were stabilized by intermolecular hydrogen bonds and stacking interactions. The amino acid residues involved in interactions were ASP1184, GLU1182, ARG1185 and SER943 for spike protein, SER1003, ALA958 and THR961 for COVID-19 main protease, and for SARS-CoV-2 (2019-nCoV) main protease, it was THR111, GLN110 and THR292. The MD simulation and MM/PBSA analysis showed that the compound seselin could effectively bind with the target receptors. The outcome of pharmacokinetic analysis suggested that the compound had favourable drugability properties. The results suggested that the seselin had inhibitory potential over multiple SARS-COV-2 targets and hold a high potential to work effectively as a novel drug for COVID-19 if evaluated in experimental setups in the foreseeable future.

Communicated by Ramaswamy H. Sarma

Keywords:

• COVID-19
• seselin
• spike protein
• main protease
• MM/PBSA

Acknowledgements

The first author gratefully acknowledges Dr Kalaignar M. Karunanidhi Endowment Scholarship (2018-19), University of Madras (No. F.11-Endow/Ph.D Scholarship/2018-19/712 dt 21 May 2019). The second author is gratified by the support of the University Grants Commission (UGC), India, for the NET-SRF (CSIR-UGC) fellowship (Certificate Sr. No. 2121530460, Ref. No: 20/12/2015(ii) EU-V).

Disclosure statement

No potential conflict of interest was reported by the authors.