Identification of Significant Mutations in Spike Protein of SARS-CoV-2 Variants of Concern and the Discovery of Potent Inhibitors

TL;DR

This study identifies key mutations in the spike protein of SARS-CoV-2 variants and discovers two promising drug candidates that could target the virus and its omicron variant.

Contribution

The study identifies shared mutations in SARS-CoV-2 spike proteins and proposes two potent inhibitors through computational docking analysis.

Findings

AZ_2 and AZ_13 showed strong binding affinity to the SARS-CoV-2 spike protein based on docking scores and interactions.

Shared mutations in the spike region of omicron and other variants were identified and structurally compared.

The proposed compounds could serve as potential remedies against SARS-CoV-2 and its omicron variant.

Abstract

Background: SARS-CoV-2 is a positive-sense single-stranded RNA virus that has a propensity for infecting epithelial cells and the respiratory system. The two important proteins, structural and nonstructural proteins, make the architecture of this virus.

Aim: This research aimed at studying significant mutations in spike protein of SARS-CoV-2 variants of concern (VoCs) and finding shared mutations among omicron and other four variants (alpha, beta, gamma, and delta). The purpose of this study was to draw structural comparisons between wild type and mutant proteins, followed by identifying potent inhibitors (ligand) that could be used against SARS-CoV-2 spike protein and its latest omicron VoC.

Methodology: In this research, we had studied 16 major mutations as well as shared mutations (6) present in spike region of SARS-CoV-2. Subsequently, we determined the structure of the wild-type SARS-CoV-2 protein from the Protein Data Bank (PDB) with the ID 7R4I. Furthermore, the structure of the mutant protein of SARS-CoV-2 omicron variant was modeled in SWISS-MODEL. The ligand dataset for spike protein of SARS-CoV-2 was also collected from literature and different databases. Both wild type and mutant proteins were docked with ligand database in Molecular Operating Environment (MOE). The docking analysis was performed, and two best ligand molecules, AZ_2 and AZ_13, were finalized based on their energy values, interactions, and docking scores to be used against our wild and mutant proteins.

Results: AZ_2 demonstrated a docking score of −6.1753 in MOE, with energy values of −4.3889 and −6.1753. It formed key hydrogen bond interactions. AZ_13 showed a docking score of −5.9, with energy values of −9.3 and −5.9, forming hydrogen donor and acceptor interactions with Asp950 (3.06 Å), Ile312 (3.13 Å), and Glu309 (3.27 Å). These interactions suggest strong binding affinity and potential efficacy. Thus, present research work emphasized on identification of significant mutations and finding a potent target-based drug against SARS-CoV-2 and its omicron variant.

Outcomes: Based on this computational analysis performed, it is suggested that proposed compound can be used as remedy against SARS-CoV-2 and its omicron variant.

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