Molecular docking is one of the most widely used computational tools in structure-based
drug design and is critically dependent on accuracy and robustness of the scoring function …

Protein–ligand scoring functions are widely used in structure-based drug design for fast
evaluation of protein–ligand interactions, and it is of strong interest to develop scoring …

Scoring functions are important components in molecular docking for structure-based drug
discovery. Traditional scoring functions, generally empirical-or force field-based, are robust …

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 …

The development of new protein–ligand scoring functions using machine learning
algorithms, such as random forest, has been of significant interest. By efficiently utilizing …

In structure-based drug design, scoring functions are often employed to evaluate protein–
ligand interactions. A variety of scoring functions have been developed so far, and thus …

Our comparative assessment of scoring functions (CASF) benchmark is created to provide
an objective evaluation of current scoring functions. The key idea of CASF is to compare the …

Computer-aided protein–ligand binding predictions are a valuable help in drug discovery.
Protein–ligand docking programs generally consist of two main components: a scoring …

We present DrugScore2018, a new version of the knowledge-based scoring function
DrugScore, which builds upon the same formalism used to derive DrugScore but exploits a …

Protein–ligand docking is a useful tool for providing atomic-level understanding of protein
functions in nature and design principles for artificial ligands or proteins with desired …