Pradipta Bandyopadhyay

This study uses molecular dynamics to compare Cu2+ and Mg2+ binding to Dickerson DNA, revealing similar binding preferences but distinct binding mechanisms for Cu2+.

The paper develops a fast and accurate method to predict Ca2+ binding sites in proteins using statistical mechanics, achieving 88% accuracy comparable to existing data-driven methods.

This paper develops an integrative model combining MD simulations, evolutionary analysis, and machine learning to predict Ca2+ binding affinity for mutations in cardiac Troponin-C, achieving accurate predictions with low error.