通过计算方面对维甲酸受体γ（RARγ）激动作用的结构要求
Structural requirement of RARγ agonism through computational aspects.
作者信息
Liu Haihan, Hu Baichun, Luan Jiasi, Sun Yuqing, Wang Shizun, Li Weixai, Chen Lu, Wang Hanxun, Gao Yinli, Wang Jian
机构信息
Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang, 110016, People's Republic of China.
Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang, 110016, China.
出版信息
J Mol Model. 2023 Mar 24;29(4):108. doi: 10.1007/s00894-023-05507-6.
CONTEXT
RARγ is a therapeutic target for many skin diseases and has potential in cancer treatment. In the current study, we put forward a comprehensive structure-activity relationship study of third and fourth generations of RARγ agonists, addressing multiple crystal structures of RARγ complexes and approved drugs. Adapalene and Trifarotene, through hybrid strategies including protein contacts Atlas analysis, molecular docking, dynamics simulations, MM-GBSA, ASM, and pharmacophore modeling. Our result revealed crucial amino acids Arg267, Ser278, Phe288, Phe230, Met272, Leu271, and Leu268 within the RARγ pocket, as well as pharmacophore features such as two hydrophobic groups, two aromatic rings, and negative ionic features, which are essential for the binding of RARγ agonists. Based on this study, the binding mechanism of RARγ agonists was elucidated, which will be helpful for the rational design of new RARγ agonists for skin diseases and cancer treatment.
METHODS
In this study, Schrödinger suite 2021-2 with OPLS_4 force field, Discovery Studio program 3.0, LigandScout 4.3, and PyMOL are utilized in the investigation.
背景
维甲酸受体γ（RARγ）是多种皮肤病的治疗靶点，在癌症治疗中也具有潜力。在本研究中，我们对第三代和第四代RARγ激动剂进行了全面的构效关系研究，涉及RARγ复合物的多个晶体结构和已获批药物。通过包括蛋白质接触图谱分析、分子对接、动力学模拟、MM-GBSA、ASM和药效团建模等混合策略，研究了阿达帕林和曲法罗汀。我们的结果揭示了RARγ口袋内的关键氨基酸精氨酸267、丝氨酸278、苯丙氨酸288、苯丙氨酸230、甲硫氨酸272、亮氨酸271和亮氨酸268，以及两个疏水基团、两个芳香环和负离子特征等药效团特征，这些对于RARγ激动剂的结合至关重要。基于本研究，阐明了RARγ激动剂的结合机制，这将有助于合理设计用于皮肤病和癌症治疗的新型RARγ激动剂。
方法
在本研究中，使用了带有OPLS_4力场的Schrödinger套件2021-2、Discovery Studio程序3.0、LigandScout 4.3和PyMOL进行研究。
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