Potterton Andrew, Heifetz Alexander, Townsend-Nicholson Andrea
Structural and Molecular Biology, University College London, Darwin Building, Gower Street, London, WC1E 6BT, UK.
Evotec (UK) Ltd., 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire, OX14 4RZ, UK.
Methods Mol Biol. 2018;1705:335-343. doi: 10.1007/978-1-4939-7465-8_15.
There is a substantial amount of historical ligand binding data available from site-directed mutagenesis (SDM) studies of many different GPCR subtypes. This information was generated prior to the wave of GPCR crystal structure, in an effort to understand ligand binding with a view to drug discovery. Concerted efforts to determine the atomic structure of GPCRs have proven extremely successful and there are now more than 80 GPCR crystal structure in the PDB database, many of which have been obtained in the presence of receptor ligands and associated G proteins. These structural data enable the generation of computational model structures for all GPCRs, including those for which crystal structures do not yet exist. The power of these models in designing novel ligands, especially those with improved residence times, and for better understanding receptor function can be enhanced tremendously by combining them synergistically with historic SDM ligand binding data. Here, we describe a protocol by which historic SDM binding data and receptor models may be used together to identify novel key residues for mutagenesis studies.
通过对许多不同GPCR亚型进行定点诱变(SDM)研究,可获得大量的历史配体结合数据。这些信息是在GPCR晶体结构浪潮之前生成的,旨在通过了解配体结合来进行药物发现。确定GPCR原子结构的协同努力已被证明极为成功,目前PDB数据库中有80多种GPCR晶体结构,其中许多是在受体配体和相关G蛋白存在的情况下获得的。这些结构数据能够为所有GPCR生成计算模型结构,包括那些尚未有晶体结构的GPCR。通过将这些模型与历史SDM配体结合数据进行协同整合,能够极大地增强其在设计新型配体(尤其是具有更长停留时间的配体)以及更好地理解受体功能方面的能力。在此,我们描述了一种方案,通过该方案可将历史SDM结合数据与受体模型一起用于识别诱变研究中的新型关键残基。