The dissociation rate (k off) associated with ligand unbinding events from proteins is a
parameter of fundamental importance in drug design. Here we review recent major …

Discovery and optimization of small molecule inhibitors as therapeutic drugs have
immensely benefited from rational structure-based drug design. With recent advances in …

Binding affinity prediction largely determines the discovery efficiency of lead compounds in
drug discovery. Recently, machine learning (ML)-based approaches have attracted much …

In the current era of high-throughput drug discovery and development, molecular modeling
has become an indispensable tool for identifying, optimizing and prioritizing small-molecule …

Prediction of protein–ligand binding affinity is a major goal in drug discovery. Generally, free
energy gap is calculated between two states (eg, ligand binding and unbinding). The energy …

Highlights•Many new approaches to computing biomolecular binding kinetics developed
recently.•Enhanced sampling simulation methods permit long-time binding kinetics to be …

The recent paradigm shift toward the use of the kinetics parameters in place of
thermodynamic constants is leading the computational chemistry community to develop …

Protein-ligand binding prediction has extensive biological significance. Binding affinity helps
in understanding the degree of protein-ligand interactions and is a useful measure in drug …

In computational drug design, ranking a series of compound analogs in a manner that is
consistent with experimental affinities remains a challenge. In this study, we evaluated the …

In the field of medicinal chemistry there is increasing focus on identifying key proteins whose
biochemical functions can firmly be linked to serious diseases. Such proteins become …