The prediction of protein–ligand binding affinities is of central interest in computer-aided
drug discovery, but it is still difficult to achieve a high degree of accuracy. Recent studies …

Software to more rapidly and accurately predict protein–ligand binding affinities is of high
interest for early-stage drug discovery, and physics-based methods are among the most …

In this paper, we review our efforts to use quantum mechanical (QM) methods to improve
free-energy estimates of the binding of drug candidates to their receptor proteins. First, we …

Ligand binding affinity prediction is one of the most important applications of computational
chemistry. However, accurately ranking compounds with respect to their estimated binding …

The calculation of binding affinities for flexible ligands has hitherto required the availability of
reliable molecular mechanics parameters for the ligands, a restriction that can in principle be …

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 …

Force field accuracy is still one of the “stalemates” in biomolecular modeling. Model systems
with high quality experimental data are valuable instruments for the validation and …

Improving the capability of atomistic computer models to predict the thermodynamics of
noncovalent binding is critical for successful structure-based drug design, and the accuracy …

The accurate prediction of protein–protein complex geometries is of major importance to
ultimately model the complete interactome of interacting proteins in a cell. A major …

One of the most important biological processes at the molecular level is the formation of
protein–ligand complexes. Therefore, determining their structure and underlying key …