Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India.
Department of Bioinformatics, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation.
Proteins. 2019 Jun;87(6):452-466. doi: 10.1002/prot.25667. Epub 2019 Feb 25.
Mutations in transmembrane proteins (TMPs) have diverse effects on their structure and functions, which may lead to various diseases. In this present study, we have investigated variations in human membrane proteins and found that negatively charged to positively charged/polar and nonpolar to nonpolar changes are dominant in disease-causing and neutral mutations, respectively. Further, we analyzed the top 10 preferred mutations in 14 different disease classes and found that each class has at least two Arg mutations. Moreover, in cardiovascular diseases and congenital disorders of metabolism, Cys mutations occur more frequently in single-pass proteins, whereas Arg and nonpolar residues are more frequently substituted in multi-pass membrane proteins. The immune system diseases are enriched in C → R and C → Y mutations in inside and outside regions. On the other hand, in the membrane region, E → K and R → Q mutations are prevalent. The comparison of mutations in topologically similar regions of globular and membrane proteins showed that Ser and Thr mutations cause deleterious effects in membrane regions, whereas Cys and charged residues, Asp and Arg are prevalent in the buried regions of globular proteins. Our comprehensive analysis of disease-associated mutations in transmembrane proteins will be useful for developing prediction tools.
跨膜蛋白 (TMP) 中的突变对其结构和功能有多种影响,可能导致各种疾病。在本研究中,我们研究了人类膜蛋白的变异,发现致病突变和中性突变分别以负电荷到正电荷/极性和非极性到非极性变化为主。此外,我们分析了 14 种不同疾病类型中的前 10 种首选突变,发现每个类型至少有两个 Arg 突变。此外,在心血管疾病和先天性代谢紊乱中,Cys 突变在单通道蛋白中更常见,而 Arg 和非极性残基在多通道膜蛋白中更常见。免疫系统疾病在内外区域富含 C→R 和 C→Y 突变。另一方面,在膜区,E→K 和 R→Q 突变很常见。球状和膜蛋白拓扑相似区域突变的比较表明,Ser 和 Thr 突变在膜区造成有害影响,而 Cys 和带电残基、Asp 和 Arg 在球状蛋白的埋藏区更为常见。我们对跨膜蛋白中与疾病相关的突变进行的综合分析将有助于开发预测工具。