Computational Drug Repurposing Predictions for Chikungunya Virus Protease

Quynh Mai Thai's dataset contains computational screening results for 1,820 FDA-approved compounds against the Chikungunya virus nsP2 protease. The data includes molecular docking scores, molecular dynamics simulation results, and free energy perturbation calculations to predict potential drug inhibitors. It was last updated on 2026-05-29.

Use Cases

• Prioritizing drug candidates for experimental validation based on docking scores and molecular dynamics stability.
• Analyzing the mechanistic interaction of small molecules and peptides with the viral protease active site.
• Comparing the predicted inhibitory performance of repurposed drugs against a reference inhibitor.

Strengths

• Includes results for 1,820 unique compounds from FDA-approved libraries.
• Provides a relative energetic ranking of six compounds predicted to outperform the reference inhibitor.
• Data is structured in an XLSX file format, which is widely accessible.

Limitations

• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The dataset is small at 58.9 KB, indicating limited scope and likely a focused set of computational results.

Provenance

Source

figshare

Collection Method

Computational drug repurposing strategy involving molecular docking screens and molecular dynamics simulations.

Freshness

Last updated 2026-05-29 07:29:33