High-Accuracy Prediction of Stabilizing Surface Mutations to the Three-Helix Bundle, UBA(1), with EmCAST
High-Accuracy Prediction of Stabilizing Surface Mutations to the Three-Helix Bundle, UBA(1), with EmCAST
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DOI：
10.1021/jacs.3c04966
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发表时间：
2023-10-10
影响因子：
15
通讯作者：
Bowler，Bruce E.
中科院分区：
文献类型：
--
作者：
Rothfuss，Michael T.;Becht，Dustin C.;Bowler，Bruce E.
蛋白质结构的能量贡献的精确建模是蛋白质分析和设计的计算方法中的一个基本挑战。我们描述了一个通用的计算方法，EmCAST（经验Cα稳定化），评分和优化序列的蛋白质结构。该方法依赖于来自所有可能的四残基序列的Cα二面角偏好数据库的经验势，使用蛋白质数据库中的数据。我们的方法产生的稳定性预测，自然相关的一对一与溶剂暴露的突变位点的实验结果。EmCAST预测了四个突变，通过优化螺旋和转角中的残基，将三螺旋束乌巴（1）的稳定性从2.4 kcal/mol增加到4.8 kcal/mol。对于一组八个变体，预测和实验稳定性非常好地相关（R2= 0.97），斜率接近1，EmCAST预测的标准误差为0.16千卡/摩尔。对文献数据的表面暴露突变的稳定性影响的测试表明，EmCAST优于现有的稳定性预测方法。将乌巴（1）变体结晶，以原子分辨率验证和分析其结构。进行热力学和动力学折叠实验，以确定稳定的幅度和机制。我们的方法有可能使快速，合理的优化天然蛋白质，扩展的序列/结构关系的分析，并补充现有的蛋白质设计策略。
The accurate modeling of energetic contributions to protein structure is a fundamental challenge in computational approaches to protein analysis and design. We describe a general computational method, EmCAST (empirical Cα stabilization), to score and optimize the sequence to the structure in proteins. The method relies on an empirical potential derived from the database of the Cα dihedral angle preferences for all possible four-residue sequences, using the data available in the Protein Data Bank. Our method produces stability predictions that naturally correlate one-to-one with the experimental results for solvent-exposed mutation sites. EmCAST predicted four mutations that increased the stability of a three-helix bundle, UBA(1), from 2.4 to 4.8 kcal/mol by optimizing residues in both helices and turns. For a set of eight variants, the predicted and experimental stabilizations correlate very well (R2= 0.97) with a slope near 1 and with a 0.16 kcal/mol standard error for EmCAST predictions. Tests against literature data for the stability effects of surface-exposed mutations show that EmCAST outperforms the existing stability prediction methods. UBA(1) variants were crystallized to verify and analyze their structures at an atomic resolution. Thermodynamic and kinetic folding experiments were performed to determine the magnitude and mechanism of stabilization. Our method has the potential to enable the rapid, rational optimization of natural proteins, expand the analysis of the sequence/structure relationship, and supplement the existing protein design strategies.