Surflex-Dock employs an empirically derived scoring function to rank putative protein−
ligand interactions by flexible docking of small molecules to proteins of known structure. The …

Empirical scoring functions used in protein-ligand docking calculations are typically trained
on a dataset of complexes with known affinities with the aim of generalizing across different …

Automated docking is one of the most important tools for structure‐based drug design that
allows prediction of ligand binding poses and also provides an estimate of how well small …

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 …

Predicting the binding affinities of large sets of diverse molecules against a range of
macromolecular targets is an extremely challenging task. The scoring functions that attempt …

A common strategy for virtual screening considers a systematic docking of a large library of
organic compounds into the target sites in protein receptors with promising leads selected …

Exploitation of protein structures for potential drug leads by molecular docking is critically
dependent on methods for scoring putative protein-ligand interactions. An ideal function for …

Applications in structural biology and medicinal chemistry require protein–ligand scoring
functions for two distinct tasks:(i) ranking different poses of a small molecule in a protein …

The ability to rapidly assess the quality of a protein‐ligand complex in terms of its affinity is of
fundamental importance for various methods of computer‐aided drug design. While simple …

The scoring functions for protein-ligand interactions plays central roles in computational
drug design, virtual screening of chemical libraries for new lead identification, and prediction …