Computational Molecular Docking Studies of Small Molecule Inhibitors With the SARS-CoV-2 Spike Protein Variants: In-Silico Drug Discovery Using Virtual Screening and Drug Repurposing Approaches

<p>The pandemic caused by the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 has caused a global public health crisis of nearly unprecedented scale. In the years following the outbreak, the scientific community has mobilized to develop several vaccines and treatments. Drug repurposing as a strategy for drug development has produced many of the current therapeutic options. The greatest challenge to designing a therapeutic inhibitor of SARS-CoV-2 is the shifting mutational landscape of the virus as it evolves. In this study, we focus on the spike protein as a target for potential inhibitors. We explore two methods of inhibiting spike function, allosteric inhibition and direct inhibition. In the study of allosteric inhibition, we screened two compound libraries against two allosteric sites. In the study of direct inhibition, several top-performing direct inhibitors of the wildtype spike were evaluated against five variants, B.1.1.7, B.1.351, P.1, B.1.617.2, and B.1.1.529. In summary, we identify four potential allosteric inhibitors that warrant further in-vitro study. We also find that the direct potential inhibitors of the wildtype spike had the most similar performance against the B.1.617.2 and B.1.1.7 variants.</p>

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computational and Data Sciences

Year

2023

Author dc:creator

• Gupta, Grace

Contributors dc:contributor

• Gennady Verkhivker
• Cyril Rakovski
• Mohamed Allali

• drug repurposing
• virtual screening
• molecular docking
• SARS-CoV-2
• spike protein
• Bioinformatics

Repository record dc:identifier

https://digitalcommons.chapman.edu/cads_theses/18

OAI identifier oai:identifier

oai:digitalcommons.chapman.edu:cads_theses-1017