title: TargetATPsite: a template-free method for ATP-binding sites prediction with residue evolution image sparse representation and classifier ensemble.
abstract: Understanding the interactions between proteins and ligands is critical for protein function annotations and drug discovery. We report a new sequence-based template-free predictor (TargetATPsite) to identify the Adenosine-5'-triphosphate (ATP) binding sites with machine-learning approaches. Two steps are implemented in TargetATPsite: binding residues and pockets predictions, respectively. To predict the binding residues, a novel image sparse representation technique is proposed to encode residue evolution information treated as the input features. An ensemble classifier constructed based on support vector machines (SVM) from multiple random under-samplings is used as the prediction model, which is effective for dealing with imbalance phenomenon between the positive and negative training samples. Compared with the existing ATP-specific sequence-based predictors, TargetATPsite is featured by the second step of possessing the capability of further identifying the binding pockets from the predicted binding residues through a spatial clustering algorithm. Experimental results on three benchmark datasets demonstrate the efficacy of TargetATPsite.
authors.affiliation: School of Computer Science and Engineering, Nanjing University of Science and Technology, Xiaolingwei 200, Nanjing 210094, China.
authors.forename: Dong-Jun
authors.initials: DJ
authors.lastname: Yu
authors.forename: Jun
authors.initials: J
authors.lastname: Hu
authors.forename: Yan
authors.initials: Y
authors.lastname: Huang
authors.forename: Hong-Bin
authors.initials: HB
authors.lastname: Shen
authors.forename: Yong
authors.initials: Y
authors.lastname: Qi
authors.forename: Zhen-Min
authors.initials: ZM
authors.lastname: Tang
authors.forename: Jing-Yu
authors.initials: JY
authors.lastname: Yang
mesh_terms: D000255:Adenosine Triphosphate / Q000737:chemistry*; D001665:Binding Sites; D030562:Databases, Protein; D015195:Drug Design; D006801:Humans; D008024:Ligands; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry*; D012984:Software; D060388:Support Vector Machine; D013816:Thermodynamics
chemical_list: D008024:Ligands; D011506:Proteins; D000255:Adenosine Triphosphate