In biotechnology applications, rational design of new proteins with improved physico-chemical properties includes a number of important tasks. One of the greatest practical and fundamental challenges is the design of highly thermostable protein enzymes that maintain catalytic activity at high temperatures. This problem may be solved by introducing mutations into the wild-type enzyme protein. In this work, to predict the impact of such mutations in barnase protein we applied the anisotropic network modeling approach, revealing atomic fluctuations in structural regions that are changed in mutants compared to the wild-type protein. A regression model was constructed based on these structural features that can allow one to predict the thermal stability of new barnase mutants. Moreover, the analysis of regression model provides a mechanistic explanation of how the structural features can contribute to the thermal stability of barnase mutants.

在生物技术应用中，合理设计具有改善的物理化学性质的新蛋白质包括许多重要任务。最大的实践和根本挑战之一是设计在高温下保持催化活性的高度热稳定的蛋白酶。通过将突变引入野生型酶蛋白中可以解决该问题。在这项工作中，为了预测此类突变对barnase蛋白的影响，我们应用了各向异性网络建模方法，揭示了与野生型蛋白相比，突变体中发生变化的结构区域的原子涨落。基于这些结构特征构建了一种回归模型，该模型可以使人们预测新的barnase突变体的热稳定性。此外，