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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。
Determining the effect of amino acid mutations on protein stability is important to understand molecular mechanisms of disease and new protein design. This research also helps to revamp and reorganize the immunological vaccine design in order to improve the stability of protein drugs in pharmacy. The experimental determination is time-consuming and expensive. Computational methods have been used to predict the effects of mutations and to elucidate their underlying biological mechanisms. This article describes two types of methods for predicting the effects of residue mutations on protein stability: the direct calculation of energy functions and machine learning methods; the 15 most up-to-date online forecasting tools and a description of the challenges and future directions.