title: Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms.
abstract: Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites.
authors: Genomics Research Center, Academia Sinica, Taipei, Taiwan 115.|Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan 11221.|Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, Taiwan 115.
authors: Jhih-Wei
authors: JW
authors: Jian
authors: Genomics Research Center, Academia Sinica, Taipei, Taiwan 115.
authors: Pavadai
authors: P
authors: Elumalai
authors: Genomics Research Center, Academia Sinica, Taipei, Taiwan 115.|Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, Taiwan 115.|Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan 30013.
authors: Thejkiran
authors: T
authors: Pitti
authors: Genomics Research Center, Academia Sinica, Taipei, Taiwan 115.
authors: Chih Yuan
authors: CY
authors: Wu
authors: Genomics Research Center, Academia Sinica, Taipei, Taiwan 115.
authors: Keng-Chang
authors: KC
authors: Tsai
authors: Genomics Research Center, Academia Sinica, Taipei, Taiwan 115.
authors: Jeng-Yih
authors: JY
authors: Chang
authors: Genomics Research Center, Academia Sinica, Taipei, Taiwan 115.
authors: Hung-Pin
authors: HP
authors: Peng
authors: Genomics Research Center, Academia Sinica, Taipei, Taiwan 115.
authors: An-Suei
authors: AS
authors: Yang
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D030562:Databases, Protein; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D008024:Ligands; D011506:Proteins