Performance of structure-based molecular docking largely depends on the accuracy of
scoring functions. One important type of scoring functions are knowledge-based potentials …

The performances of several two-step scoring approaches for molecular docking were
assessed for their ability to predict binding geometries and free energies. Two new scoring …

The growing number of protein–ligand complex structures, particularly the structures of
proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major …

A major challenge in the field of protein–protein docking is to discriminate between the many
wrong and few near-native conformations, ie scoring. Here, we introduce combinatorial …

Predicting conformational changes of both the protein and the ligand is a major challenge
when a protein–ligand complex structure is predicted from the unbound protein and ligand …

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 …

Accurate protein binding structure determination presents a great challenge to both
experiment and theory. Here, in this work, we propose a new DOX protocol which combines …

As one of the most popular computational approaches in modern structure-based drug
design, molecular docking can be used not only to identify the correct conformation of a …

Background Computational approaches to protein-protein docking typically include scoring
aimed at improving the rank of the near-native structure relative to the false-positive …

Using a novel iterative method, we have developed a knowledge‐based scoring function
(ITScore) to predict protein–ligand interactions. The pair potentials for ITScore were derived …