title: Construction of a three-dimensional pharmacophore for Bcl-2 inhibitors by flexible docking and the multiple copy simultaneous search method.
abstract: B-Cell lymphoma-2 (Bcl-2) protein is a new promising target for anticancer drugs. A number of anticancer Bcl-2 inhibitors with diverse chemical structures have been discovered in recent years. In this paper, the flexible docking was performed to determine the binding modes of the representative inhibitors from different structural types. Subsequently, the binding modes of inhibitor were used to construct a primary three- dimensional (3D) pharmacophore model. It proved that this model can effectively disrupt the binding of the BH3 domain of proapoptotic Bcl-2 family members to Bcl-2, and match the structural requirement of a new type of Bcl-2 inhibitors. However, these distances between pharmacophoric points are not optimal due to the fact that not all of individual functional groups are located in the ideal position when inhibitors bind to its receptor. In this paper, we proposed a new idea to improve the quality of the pharmacophore model: the multiple copy simultaneous search (MCSS) method was performed to determine the energetically favorable distribution of functional groups with similar features to these pharmacophoric points in the active site of Bcl-2 first. Then their most energetically favorable minima in the positions near the pharmacophoric points were used to optimize the distances between pharmacophoric points. By examining the binding modes of several inhibitors from the same structural type, it was found that the more potent the inhibitor was, the closer it was to the optimized distances between pharmacophoric points. The optimized 3D pharmacophore model obtained in this paper may provide a good starting point for further rational design of Bcl-2 inhibitors.
authors.affiliation: Department of Medicinal Chemistry, School of Pharmacy, Second Military Medical University, 325 Guohe Road, Shanghai 200433, China.
authors.forename: Can-Hui
authors.initials: CH
authors.lastname: Zheng
authors.forename: You-Jun
authors.initials: YJ
authors.lastname: Zhou
authors.forename: Ju
authors.initials: J
authors.lastname: Zhu
authors.forename: Hai-Tao
authors.initials: HT
authors.lastname: Ji
authors.forename: Jun
authors.initials: J
authors.lastname: Chen
authors.forename: Yao-Wu
authors.initials: YW
authors.lastname: Li
authors.forename: Chun-Quan
authors.initials: CQ
authors.lastname: Sheng
authors.forename: Jia-Guo
authors.initials: JG
authors.lastname: Lu
authors.forename: Jun-Hang
authors.initials: JH
authors.lastname: Jiang
authors.forename: Hui
authors.initials: H
authors.lastname: Tang
authors.forename: Yun-Long
authors.initials: YL
authors.lastname: Song
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000737:chemistry / Q000494:pharmacology*; D001665:Binding Sites; D003198:Computer Simulation; D016208:Databases, Factual; D015195:Drug Design; D004791:Enzyme Inhibitors / Q000737:chemistry / Q000494:pharmacology*; D006860:Hydrogen Bonding; D016393:Lymphoma, B-Cell / Q000737:chemistry / Q000378:metabolism*; D009682:Magnetic Resonance Spectroscopy; D008956:Models, Chemical
chemical_list: D000970:Antineoplastic Agents; D004791:Enzyme Inhibitors