报告题目：Impact of SNP mutations on Protein Folding and Human Diseases

报告人：张阳教授，密歇根大学

报告时间：2019年7月31日，下午：14:00

报告地点：信息学院D533学术报告厅

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报告摘要：

Mutation and evolution in the human genome are mainly through single nucleotide polymorphisms (SNPs). Some SNP mutations can affect the folding stability of proteins and the binding affinity of protein-protein interactions, which have caused more than 6,000 human diseases including cancer, diabetes and obesity. We propose a new approach to modeling the SNP-induced binding and folding stability changes by considering the evolutionary profiles that are collected from multiple alignments of homologous protein structures and protein-protein interfaces. The approach was applied to 3,421 SNPs affecting protein folding stability and 1,402 multi-mutations involved in protein-protein interfaces. It was shown that the calculated Gibbs free-energy changes between wide-type and mutant proteins, ΔΔG, have a strong correlation coefficient (~0.8) and a low root-mean-square error ~1.2 kcal/mol, compared to the experimentally characterized ΔΔG values. When incorporating the profiling features with deep-learning technique, the method is able to correctly recognize 80% of the disease-associated mutations from 10,635 SNPs involved in the human genome, with the Matthew’s correlation coefficient (0.6) significantly higher than that deduced by physics-based approaches. These data demonstrate significant potential and advantage of using evolutionary profiles to investigate the impact of SNP mutations on protein folding and interaction, and human diseases.

报告人简介：

张阳，美国密歇根大学计算医学与生物信息学系以及生物化学系教授。在蛋白质折叠和结构预测、蛋白质设计、以及功能注解等方向开展了一系列开拓性的研究，并产生了重要的国际影响。I-TASSER发明人（I-TASSER在国际蛋白质结构预测CASP大赛自动组中连续六届名列第一，在生物信息及生物医学领域得到广泛应用）。主持与完成NIH百万美元以上级项目研究课题10余项。曾获得NSF早期生涯奖、斯隆奖、以及密歇根大学基础科学奖等奖项；担任IEEE/ACM Transactions on Computational Biology and Bioinformatics、Journal of Structural Biology等8种国际期刊的编委。在Nature Methods，PNAS等著名期刊上发表论文160多篇，被国际同行引用两万三千余次。连续四年入选2015，2016，2017和2018年度汤森路透（Thomson Reuters）全球高被引科学家。