HotLig: a molecular surface-directed approach to scoring protein-ligand interactions.

Accurate prediction of ligand-binding poses is crucial for understanding molecular interactions and is very important for drug discovery, structural design, and optimization. In this study, we developed a novel scoring program, HotLig, which applies the Connolly surface of a protein to calculate hydrophobic interaction and paired pharmacophore interactions with ligands. In addition to molecular surface distance, ligand-contacting areas and hydrogen-bond angles were also introduced to the scoring functions in HotLig. Four individual energy scoring functions for H-bonds, ionic pairs, metal coordination, and hydrophobic effects were derived from 600 protein–ligand complexes, and then, their weighting factors were optimized through an interaction-characterized training set. Success rates of ligand-binding-pose predictions (with a root mean squared deviation of ≤2 A) for the Wang, GOLD, and Cheng data sets were respectively validated to be 91.0%, 87.0%, and 85.6%. HotLig was found to possess equally good predi...