氨基酸突变对蛋白质稳定性的影响预测及其在线工具

Prediction of protein stability changes upon mutations and its web-based tools

确定氨基酸突变对蛋白质稳定性的影响对于分子水平的疾病机理理解和新蛋白质设计是十分重要的。这项研究也有助于药物学上的为提高蛋白质药物的稳定性而对其进行的改造与重组以及免疫学上的疫苗设计。实验测定费时费力且代价昂贵。计算方法已用来预测突变的影响和阐明其潜在的生物学机制。本文阐述预测残基突变对蛋白质稳定性影响的两类方法:使用能量函数直接计算法和机器学习方法;介绍15个最新在线预测工具并说明面临的挑战与未来的方向。

It is very important to determine protein stability changes upon mutations for understanding the molecular underpinnings of diseases and designing of new proteins. It is also helpful for the research of modifying and recombinant of protein agents which increases its stability on pharmacology and for immunological vaccine design. Experimental studies on the protein stability changes upon mutations are often laborious, time-consuming, and costly. In recent years, computational methods are used to predict the effects caused by mutations and to elucidate the underlying biological mechanisms. First, this paper illustrates current prediction methods for protein stability changes upon mutations by giving some examples, including energy-based methods and machine learning approaches. Next, it presents 15 latest web-based tools related to the prediction, and then discusses challenges and the direction of the future development.