Structural Bioinformatics Group, Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Sir Ernst Chain Building, Imperial College London, London SW7 2AZ, UK.
Structural Bioinformatics Group, Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Sir Ernst Chain Building, Imperial College London, London SW7 2AZ, UK.
J Mol Biol. 2019 May 17;431(11):2197-2212. doi: 10.1016/j.jmb.2019.04.009. Epub 2019 Apr 14.
Knowledge of protein structure can be used to predict the phenotypic consequence of a missense variant. Since structural coverage of the human proteome can be roughly tripled to over 50% of the residues if homology-predicted structures are included in addition to experimentally determined coordinates, it is important to assess the reliability of using predicted models when analyzing missense variants. Accordingly, we assess whether a missense variant is structurally damaging by using experimental and predicted structures. We considered 606 experimental structures and show that 40% of the 1965 disease-associated missense variants analyzed have a structurally damaging change in the mutant structure. Only 11% of the 2134 neutral variants are structurally damaging. Importantly, similar results are obtained when 1052 structures predicted using Phyre2 algorithm were used, even when the model shares low (<40%) sequence identity to the template. Thus, structure-based analysis of the effects of missense variants can be effectively applied to homology models. Our in-house pipeline, Missense3D, for structurally assessing missense variants was made available at http://www.sbg.bio.ic.ac.uk/~missense3d.
蛋白质结构的知识可用于预测错义变异的表型后果。由于如果除实验确定的坐标外还包括同源预测结构,则人类蛋白质组的结构覆盖率可以大致增加三倍以上,达到 50%以上,因此在分析错义变异时评估使用预测模型的可靠性非常重要。因此,我们使用实验和预测结构来评估错义变异是否具有结构破坏性。我们考虑了 606 个实验结构,并表明在分析的 1965 个与疾病相关的错义变异中,有 40%的突变体结构发生了结构破坏性变化。只有 11%的 2134 个中性变异具有结构破坏性。重要的是,当使用 Phyre2 算法预测的 1052 个结构时,也会得到类似的结果,即使模型与模板的序列同一性较低(<40%)。因此,基于结构的错义变异影响分析可以有效地应用于同源模型。我们的内部管道 Missense3D 可用于对错义变异进行结构评估,其网址为 http://www.sbg.bio.ic.ac.uk/~missense3d。