Worth Catherine L, Bickerton G Richard J, Schreyer Adrian, Forman Julia R, Cheng Tammy M K, Lee Semin, Gong Sungsam, Burke David F, Blundell Tom L
Biocomputing Group, Department of Biochemistry, University of Cambridge, Cambridge, UK.
J Bioinform Comput Biol. 2007 Dec;5(6):1297-318. doi: 10.1142/s0219720007003120.
The prediction of the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) on function depends critically on exploiting all information available on the three-dimensional structures of proteins. We describe software and databases for the analysis of nsSNPs that allow a user to move from SNP to sequence to structure to function. In both structure prediction and the analysis of the effects of nsSNPs, we exploit information about protein evolution, in particular, that derived from investigations on the relation of sequence to structure gained from the study of amino acid substitutions in divergent evolution. The techniques developed in our laboratory have allowed fast and automated sequence-structure homology recognition to identify templates and to perform comparative modeling; as well as simple, robust, and generally applicable algorithms to assess the likely impact of amino acid substitutions on structure and interactions. We describe our strategy for approaching the relationship between SNPs and disease, and the results of benchmarking our approach -- human proteins of known structure and recognized mutation.
非同义单核苷酸多态性（nsSNPs）对功能影响的预测，关键取决于利用蛋白质三维结构上的所有可用信息。我们描述了用于分析nsSNPs的软件和数据库，这些软件和数据库允许用户从SNP到序列，再到结构，最后到功能进行研究。在结构预测和nsSNPs效应分析中，我们利用了有关蛋白质进化的信息，特别是从对不同进化中氨基酸替换所获序列与结构关系的研究中得出的信息。我们实验室开发的技术，已实现了快速自动化的序列-结构同源性识别，以确定模板并进行比较建模；同时还开发了简单、稳健且普遍适用的算法，以评估氨基酸替换对结构和相互作用的可能影响。我们描述了处理SNP与疾病之间关系的策略，以及对我们的方法进行基准测试的结果——已知结构和公认突变的人类蛋白质。
