Predicting the geometry of protein–ligand binding complexes is of primary importance for
structure-based drug discovery. Molecular dynamics (MD) is emerging as a reliable …

Binding kinetic parameters can be correlated with drug efficacy, which in recent years led to
the development of various computational methods for predicting binding kinetic rates and …

Multicanonical molecular dynamics (McMD)-based dynamic docking has been applied to
predict the native binding configurations for several protein receptors and their ligands. Due …

A growing consensus is emerging that optimizing the drug–target affinity alone under
equilibrium conditions does not necessarily translate into higher potency in vivo and that …

Most early-stage drug discovery projects focus on equilibrium binding affinity to the target
alongside selectivity and other pharmaceutical properties. Since many approved drugs have …

Background: Calculation of ligand-binding affinity is an open problem in computational
medicinal chemistry. The ability to computationally predict affinities has a beneficial impact …

The residence time of a ligand–protein complex is a crucial aspect in determining biological
effect in vivo. Despite its importance, the prediction of ligand k off still remains challenging …

We present a multistep protocol, combining Monte Carlo and molecular dynamics
simulations, for the estimation of absolute binding free energies, one of the most significant …

Computer simulation approaches in biomolecular recognition processes have come a long
way. In this Perspective, we highlight a series of recent success stories in which computer …

The prediction of a ligand's binding mode into its macromolecular target is essential in
structure-based drug discovery. Even though tremendous effort has been made to address …