title: ID-Score: a new empirical scoring function based on a comprehensive set of descriptors related to protein-ligand interactions.
abstract: Scoring functions have been widely used to assess protein-ligand binding affinity in structure-based drug discovery. However, currently commonly used scoring functions face some challenges including poor correlation between calculated scores and experimental binding affinities, target-dependent performance, and low sensitivity to analogues. In this account, we propose a new empirical scoring function termed ID-Score. ID-Score was established based on a comprehensive set of descriptors related to protein-ligand interactions; these descriptors cover nine categories: van der Waals interaction, hydrogen-bonding interaction, electrostatic interaction, π-system interaction, metal-ligand bonding interaction, desolvation effect, entropic loss effect, shape matching, and surface property matching. A total of 2278 complexes were used as the training set, and a modified support vector regression (SVR) algorithm was used to fit the experimental binding affinities. Evaluation results showed that ID-Score outperformed other selected commonly used scoring functions on a benchmark test set and showed considerable performance on a large independent test set. ID-Score also showed a consistent higher performance across different biological targets. Besides, it could correctly differentiate structurally similar ligands, indicating higher sensitivity to analogues. Collectively, the better performance of ID-Score enables it as a useful tool in assessing protein-ligand binding affinity in structure-based drug discovery as well as in lead optimization.
authors: State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical School, Sichuan University, Sichuan 610041, China.
authors: Guo-Bo
authors: GB
authors: Li
authors: Ling-Ling
authors: LL
authors: Yang
authors: Wen-Jing
authors: WJ
authors: Wang
authors: Lin-Li
authors: LL
authors: Li
authors: Sheng-Yong
authors: SY
authors: Yang
mesh_terms: D000465:Algorithms; D018360:Crystallography, X-Ray; D030562:Databases, Protein; D019277:Entropy; D006860:Hydrogen Bonding; D008024:Ligands; D017711:Nonlinear Dynamics; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D060388:Support Vector Machine
chemical_list: D008024:Ligands; D011506:Proteins