Screening of potential ligands from the ZINC database with RAC1B using molecular docking and dynamics simulation analysis
Kajal Verma, Lakshmi Pillai
TL;DR
This study identifies five potential drug candidates that bind well to RAC1B, a protein linked to breast cancer, using computational methods.
Contribution
The study introduces five novel lead compounds from the ZINC database with strong binding affinity to RAC1B.
Findings
Five lead compounds from ZINC showed optimal binding to RAC1B.
Molecular docking and dynamics simulations confirmed the stability of these ligand-protein interactions.
These compounds are proposed for further experimental validation as potential breast cancer therapeutics.
Abstract
Breast cancer remains the most frequently diagnosed cancer among women worldwide. Therefore, it is of interest to document the Screening for potential ligands from the ZINC database with RAC1B using molecular docking and dynamics simulation analysis. Data shows the optimal binding of five lead compounds ZINC5277811, ZINC16485670, ZINC20530618, ZINC29990274, and ZINC3528881 with RAC1B for further consideration.
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsComputational Drug Discovery Methods · Machine Learning in Bioinformatics · Synthesis and biological activity