Molecules against Covid-19: An in silico approach for drug development

Rhythm Bharti, Sandeep Kumar Shukla

10.1016/j.jnlest.2021.100095

Research curated

Abstract

A large number of deaths have been caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide, turning it into a serious and momentous threat to public health. This study tends to contribute to the development of effective treatment strategies through a computational approach, investigating the mechanisms in relation to the binding and subsequent inhibition of SARS-CoV-2 ribonucleic acid (RNA)-dependent RNA polymerase (RdRp). Molecular docking was performed to screen six naturally occurring molecules with antineoplastic properties (Ellipticine, Ecteinascidin, Homoharringtonine, Dolastatin 10, Halichondrin, and Plicamycin). Absorption, distribution, metabolism, and excretion (ADME) investigation was also conducted to analyze the drug-like properties of these compounds. The docked results have clearly shown binding of ligands to the SARS-CoV-2 RdRp protein. Interestingly, all ligands were found to obey Lipinski’s rule of five. These results provide a basis for repurposing and using molecules, derived from plants and animals, as a potential treatment for the coronavirus disease 2019 (COVID-19) infection as they could be effective therapeutics for the same.

Source: PMC

Related molecules

Name	Synonyms	Genes
Ellipticine
Trabectedin	Ecteinascidin,Yondelis
Omacetaxine mepesuccinate	Homoharringtonine
Dolastatin 10
Halichondrin B
Plicamycin
RNA dependent RNA polymerase	RDR, viral RNA polymerase, RdRp, nsp12	rep, ORF1a-1b, RdRp

Related interactions

Target	Drug	Type	Result
RNA dependent RNA polymerase	Trabectedin	Computational	positive
RNA dependent RNA polymerase	Omacetaxine mepesuccinate	Computational	positive
RNA dependent RNA polymerase	Dolastatin 10	Computational	positive
RNA dependent RNA polymerase	Halichondrin B	Computational	positive
RNA dependent RNA polymerase	Plicamycin	Computational	positive