Multi-Target Ligand Screening Against SARS-CoV-2 Main Protease and Other Targets

Approximately 7,100 molecules, including Ayurvedic medicines, antiviral phytochemicals, and synthetic drugs, were screened against the SARS-CoV-2 main protease. The dataset likely contains results from computational screening, identifying natural molecules like δ-Viniferin and Myricitrin as strong binders. The research was conducted by Rakesh S. Joshi of the National Chemical Laboratory.

Use Cases

• Identifying potential drug candidates for SARS-CoV-2 based on binding affinity to the main protease.
• Repurposing existing antiviral compounds based on structural conservation of the protease binding site.
• Discovering multi-target-directed ligands based on predicted binding to RdRp and hACE-2 targets.
• Analyzing the relationship between phylogenetic clustering of coronaviruses and protease inhibitor efficacy.

Strengths

• Screens a large set of ~7,100 diverse molecules, including natural products.
• Focuses on a structurally conserved and critical drug target (SARS-CoV-2 main protease).
• Includes multi-target analysis by evaluating binding to RdRp and hACE-2.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

National Chemical Laboratory

Collection Method

Computational screening via phylogenetic, SSN analysis, and molecular docking.