力场(虚构)
焓
化学
蛋白质稳定性
系统发育树
分子动力学
理论(学习稳定性)
计算生物学
计算化学
生物
热力学
计算机科学
物理
生物化学
基因
机器学习
人工智能
作者
Koen Beerens,Stanislav Mazurenko,Antonín Kunka,Sérgio M. Marques,Niels Hansen,Miloš Musil,Radka Chaloupková,Jitka Waterman,Jan Brezovský,David Bednář,Zbyněk Prokop,Jir̆ı́ Damborský
出处
期刊:ACS Catalysis
[American Chemical Society]
日期:2018-08-31
卷期号:8 (10): 9420-9428
被引量:32
标识
DOI:10.1021/acscatal.8b01677
摘要
Stability is one of the most important characteristics of proteins employed as biocatalysts, biotherapeutics, and biomaterials, and the role of computational approaches in modifying protein stability is rapidly expanding. We have recently identified stabilizing mutations in haloalkane dehalogenase DhaA using phylogenetic analysis but were not able to reproduce the effects of these mutations using force-field calculations. Here we tested four different hypotheses to explain the molecular basis of stabilization using structural, biochemical, biophysical, and computational analyses. We demonstrate that stabilization of DhaA by the mutations identified using the phylogenetic analysis is driven by both entropy and enthalpy contributions, in contrast to primarily enthalpy-driven stabilization by mutations designed by the force-field calculations. Comprehensive bioinformatics analysis revealed that more than half (53%) of 1 099 evolution-based stabilizing mutations would be evaluated as destabilizing by force-field calculations. Thermodynamic integration considers both folded and unfolded states and can describe the entropic component of stabilization, yet it is not suitable for predictive purposes due to its high computational demands. Altogether, our results strongly suggest that energetic calculations should be complemented by a phylogenetic analysis in protein-stabilization endeavors.
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