Lulu Guan,Dushuo Feng,Jingxuan Ge,Bote Qi,Yunxiang Sun,Yu Zou
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引用次数: 0
Abstract
The serotonin 1A receptor (5-HT1AR) is involved in a wide range of physiological processes, and it has attracted considerable attention as an important target for developing new medicines. The antagonists of 5-HT1AR display therapeutic potential in depression and cognitive dysfunction, and the elucidation of their interaction with the receptor is crucial to understand pharmacological actions and develop novel therapeutic agents. Herein, we performed conventional molecular docking and molecular dynamics (MD) simulations to address the docking pose and binding mechanisms of six representative antagonists (way100635, way101405, lecozotan, nan190, sdz216-525, and nad299) to 5-HT1AR. We found that among the six antagonists, sdz216-525 exhibited the most negative docking score at -9.5 kcal/mol, while nad299 displayed the least negative score. The common pharmacophore aromatic group appeared in all six antagonists, and piperazine existed in the five antagonists except for nad299. MD simulation results showed that upon the addition of antagonists, the conformation of 5-HT1AR was changed to various extents, and the relative positions of transmembrane 3 (TM3), TM5, and TM6 underwent rearrangement. Among these antagonists, lecozotan exhibited the highest binding affinity to 5-HT1AR, whereas nad299 showed the weakest interaction. The molecular recognition of six antagonists by 5-HT1AR involved different binding patterns, with variable contributions from hydrophobic, H-bonding, cation-π/anion-π, and aromatic stacking interactions. Taken together, our computational study contributes to the understanding of the binding mechanism of antagonists to 5-HT1AR, which may facilitate the design of new antagonists targeting 5-HT1AR.
期刊介绍:
The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery.
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