title: GemAffinity: a scoring function for predicting binding affinity and virtual screening.
abstract: Prediction of protein-ligand binding affinities plays an essential role for molecular recognition and virtual screening. We have developed a scoring function, namely GemAffinity, to predict binding affinities by using a stepwise regression method and 88 descriptors from 891 complex structures. GemAffinity consists of five descriptors, including van der Waals contacts; metal-ligand interactions; water effects; ligand deformation penalty; and conserved hydrogen-bonded residues. Experimental results indicate that GemAffinity is the best among 13 methods on a test set and can enrich screening accuracies on four sets. We believe that GemAffinity is useful for virtual screening and drug discovery.
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu 30050, Taiwan. piki.bi96g@nctu.edu.tw
authors.forename: Kai-Cheng
authors.initials: KC
authors.lastname: Hsu
authors.forename: Yen-Fu
authors.initials: YF
authors.lastname: Chen
authors.forename: Jinn-Moon
authors.initials: JM
authors.lastname: Yang
mesh_terms: D001665:Binding Sites; D006860:Hydrogen Bonding; D008024:Ligands; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D008024:Ligands; D011506:Proteins