Article Publish Status: FREE
Abstract Title:

Computationally approached inhibition potential oftowards COVID-19 targets.

Abstract Source:

Virusdisease. 2021 Mar 20:1-13. Epub 2021 Mar 20. PMID: 33778129

Abstract Author(s):

Sushovan Jena, Punnagai Munusami, Balamurali Mm, Kaushik Chanda

Article Affiliation:

Sushovan Jena


: The recent emergence of novel coronavirus (SARS-CoV-2) has been a major threat to human society, as the challenge of finding suitable drug or vaccine is not met till date. With increasing morbidity and mortality, the need for novel drug candidates is under great demand. The investigations are progressing towards COVID-19 therapeutics. Among the various strategies employed, the use of repurposed drugs is competing along with novel drug inventions. Based on the therapeutic significance, the chemical constituents from the extract ofbelonging to various classes like alkaloids, lignans, steroids and terpenoids are investigated as potential drug candidates for COVID-19. The inhibition potential of the proposed compounds against viral spike protein and human receptor ACE2 were evaluated by computational molecular modeling (Auto dock), along with their ADME/T properties. Prior to docking, the initial geometry of the compounds were optimized by Density functional theory (DFT) method employing B3LYP hybrid functional and 6-311 +  + G (d,p) basis set. The results of molecular docking and ADME/T studies have revealed 6 constituents as potential drug candidates that can inhibit the binding of SARS-CoV-2 spike protein with the human receptor ACE2 protein. The narrowed down list of constituents frompaved way for further tuning their ability to inhibit COVID-19 by modifying the chemical structures and by employing computational geometry optimization and docking methods.

Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-021-00666-7.

Study Type : In Vitro Study

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