title: Molecular design of new aggrecanases-2 inhibitors.
abstract: Aggrecanases-2 is a very important potential drug target for the treatment of osteoarthritis. In this study, a series of known aggrecanases-2 inhibitors was analyzed by the technologies of three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking. Two 3D-QSAR models, which based on comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods, were established. Molecular docking was employed to explore the details of the interaction between inhibitors and aggrecanases-2 protein. According to the analyses for these models, several new potential inhibitors with higher activity predicted were designed, and were supported by the simulation of molecular docking. This work propose the fast and effective approach to design and prediction for new potential inhibitors, and the study of the interaction mechanism provide a better understanding for the inhibitors binding into the target protein, which will be useful for the structure-based drug design and modifications.
authors: College of Chemistry & Chemical Engineering, Lanzhou University, Lanzhou 730000, PR China.
authors: Zhi Jie
authors: ZJ
authors: Shan
authors: Hong Lin
authors: HL
authors: Zhai
authors: Xiao Yan
authors: XY
authors: Huang
authors: Li Na
authors: LN
authors: Li
authors: Xiao Yun
authors: XY
authors: Zhang
mesh_terms: D051722:ADAM Proteins / Q000037:antagonists & inhibitors*; D000071116:ADAMTS5 Protein; D003198:Computer Simulation; D015195:Drug Design; D004789:Enzyme Activation / Q000187:drug effects; D004791:Enzyme Inhibitors / Q000737:chemistry* / Q000494:pharmacology; D006801:Humans; D008958:Models, Molecular; D011485:Protein Binding / Q000187:drug effects; D021281:Quantitative Structure-Activity Relationship
chemical_list: D004791:Enzyme Inhibitors; D051722:ADAM Proteins; D000071116:ADAMTS5 Protein; C121532:ADAMTS5 protein, human
keywords: Aggrecanase-2; Inhibitor; Molecular design; Molecular docking; Quantitative structure–activity relationship