Here, we present FireDock, an efficient method for the refinement and rescoring of rigid‐
body docking solutions. The refinement process consists of two main steps:(1) …

Docking programs are widely used to discover novel ligands efficiently and can predict
protein− ligand complex structures with reasonable accuracy and speed. However, there is …

The performance of docking calculations can be improved by tuning parameters for the
system of interest, eg biasing the results towards the formation of relevant protein–ligand …

Training machine learning algorithms with protein–ligand descriptors has recently gained
considerable attention to predict binding constants from atomic coordinates. Starting from a …

We present results of testing the ability of eleven popular scoring functions to predict native
docked positions using a recently developed method (Ruvinsky and Kozintsev, J Comput …

Virtual screening by molecular docking has become established as a method for drug lead
discovery and optimization. All docking algorithms make use of a scoring function in …

Computational methods have become standard in today's medicinal chemistry tool kit. Like
any tool, it is important to periodically evaluate utility and ask how function can be improved …

Background In drug design, an efficient structure-based optimization of a ligand needs the
precise knowledge of the protein–ligand interactions. In the absence of experimental …

Protein binding sites undergo ligand specific conformational changes upon ligand binding.
However, most docking protocols rely on a fixed conformation of the receptor, or on the prior …

In recent years, machine-learning-based scoring functions have significantly improved the
scoring power. However, many of these methods do not perform well in distinguishing the …