On human disease-causing amino acid variants: statistical study of sequence and structural patterns.
On human disease-causing amino acid variants: statistical study of sequence and structural patterns.
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DOI：
10.1002/humu.22770
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发表时间：
2015-05
期刊：
影响因子：
3.9
通讯作者：
Alexov, Emil
中科院分区：
文献类型：
--
作者：
Petukh, Marharyta;Kucukkal, Tugba G.;Alexov, Emil
对大量天然存在的人氨基酸变异进行统计分析，并证明存在与疾病相关的某些氨基酸取代的偏好。在氨基酸序列水平上，已经表明致病变体经常涉及蛋白质的氨基酸物理化学性质的剧烈变化，例如电荷、疏水性和几何形状。对与疾病相关且在人群中常见的变异体的结构分析显示了类似的趋势：与无害的氨基酸突变相比，致病变异体倾向于引起更多的氢键网络和盐桥的变化。文献中报道的热力学数据的分析，实验和计算，表明致病的变体倾向于破坏蛋白质及其相互作用，这促使我们研究氨基酸突变对实验测量的不相关蛋白质能量变化的大型数据库的影响。尽管实验数据集既不与疾病有关，也不排除与人类蛋白质有关，但观察到的趋势是相同的：氨基酸突变往往会破坏蛋白质及其相互作用的稳定。考虑到结构和热力学性质是相互关联的，指出它们中任何一个的任何大的变化都可能导致疾病。
Statistical analysis was carried out on large set of naturally occurring human amino acid variations and it was demonstrated that there is a preference for some amino acid substitutions to be associated with diseases. At an amino acid sequence level, it was shown that the disease-causing variants frequently involve drastic changes of amino acid physico-chemical properties of proteins such as charge, hydrophobicity and geometry. Structural analysis of variants involved in diseases and being frequently observed in human population showed similar trends: disease-causing variants tend to cause more changes of hydrogen bond network and salt bridges as compared with harmless amino acid mutations. Analysis of thermodynamics data reported in literature, both experimental and computational, indicated that disease-causing variants tend to destabilize proteins and their interactions, which prompted us to investigate the effects of amino acid mutations on large databases of experimentally measured energy changes in unrelated proteins. Although the experimental datasets were linked neither to diseases nor exclusory to human proteins, the observed trends were the same: amino acid mutations tend to destabilize proteins and their interactions. Having in mind that structural and thermodynamics properties are interrelated, it is pointed out that any large change of any of them is anticipated to cause a disease.
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