Computational Screening of Phytochemicals as Potential Inhibitors of SARS-CoV-2 Main Protease

This research focuses on using computational drug discovery methods to identify plant-derived compounds (phytochemicals) that could inhibit the main protease (Mpro) of SARS-CoV-2 — an enzyme critical for the virus’s replication.

With COVID-19 impacting millions worldwide, there has been an urgent need to find safe, effective, and affordable antiviral treatments. Phytochemicals, known for their antiviral and anti-inflammatory properties, represent a promising source for new drug leads. This project explored whether natural compounds could be computationally screened to pinpoint potential therapeutic candidates faster than traditional lab methods.

I built a computational pipeline using tools like AutoDock Vina, GROMACS, and SwissADME to analyze a curated library of 50 phytochemicals.The process included:

• Molecular docking to test how tightly each compound could bind to the active site of the viral Mpro enzyme.

• Molecular dynamics simulations (100 ns) to check the stability of the protein-ligand complexes over time.

• MM-PBSA binding free energy calculations to evaluate the strength of the interactions.

• ADMET profiling to predict drug-likeness, safety, and absorption properties.

• Top candidates:

  • Withanoside V

  • Kaempferol-3-O-rutinoside

• These two compounds showed:

  • High binding affinity (strong and stable attachment to Mpro).

  • Favorable pharmacokinetic properties like good absorption and low predicted toxicity.

  • Strong hydrogen bonding and stable structures during simulations.

Other compounds, like Racemoside A and Shatavarin IX, performed well in docking but had lower oral bioavailability due to higher molecular weights.

Read more about the paper here: https://www.ijert.org/a-breath-of-fresh-air-community-driven-co2-filtration-for-cleaner-urban-environments