Application of an Integrated GPCR SAR-Modeling Platform To Explain the Activation Selectivity of Human 5-HT2C over 5-HT2B

详细信息    查看全文

• 作者：Alexander Heifetz ; R. Ian Storer ; Gordon McMurray ; Tim James ; Inaki Morao ; Matteo Aldeghi ; Mike J. Bodkin ; Philip C. Biggin
• 刊名：ACS Chemical Biology
• 出版年：2016
• 出版时间：May 20, 2016
• 年：2016
• 卷：11
• 期：5
• 页码：1372-1382
• 全文大小：765K
• 年卷期：0
• ISSN：1554-8937

文摘

Agonism of the 5-HT_2C serotonin receptor has been associated with the treatment of a number of diseases including obesity, psychiatric disorders, sexual health, and urology. However, the development of effective 5-HT_2C agonists has been hampered by the difficulty in obtaining selectivity over the closely related 5-HT_2B receptor, agonism of which is associated with irreversible cardiac valvulopathy. Understanding how to design selective agonists requires exploration of the structural features governing the functional uniqueness of the target receptor relative to related off targets. X-ray crystallography, the major experimental source of structural information, is a slow and challenging process for integral membrane proteins, and so is currently not feasible for every GPCR or GPCR–ligand complex. Therefore, the integration of existing ligand SAR data with GPCR modeling can be a practical alternative to provide this essential structural insight. To demonstrate this, we integrated SAR data from 39 azepine series 5-HT_2C agonists, comprising both selective and unselective examples, with our hierarchical GPCR modeling protocol (HGMP). Through this work we have been able to demonstrate how relatively small differences in the amino acid sequences of GPCRs can lead to significant differences in secondary structure and function, as supported by experimental data. In particular, this study suggests that conformational differences in the tilt of TM7 between 5-HT_2B and 5-HT_2C, which result from differences in interhelical interactions, may be the major source of selectivity in G-protein activation between these two receptors. Our approach also demonstrates how the use of GPCR models in conjunction with SAR data can be used to explain activity cliffs.