Insights of conformational dynamics on catalytic activity in the computational stability design of Bacillus subtilis LipA

被引:6
|
作者
Dong, Fangying [1 ]
Zhang, Meng [1 ]
Ma, Rui [1 ]
Lu, Cheng [1 ]
Xu, Fei [1 ]
机构
[1] Jiangnan Univ, Sch Biotechnol, Key Lab Carbohydrate Chem & Biotechnol, Minist Educ, Wuxi 214122, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Molecular dynamics; Protein stability; Enzyme catalysis; Bacillus subtilis LipA; Conformational dynamics; Activity-stability trade-off; MOLECULAR-DYNAMICS; PROTEIN; ENZYME; THERMOSTABILITY; SIMULATIONS; PREDICTION; EVOLUTION;
D O I
10.1016/j.abb.2022.109196
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In protein engineering, the contributions of individual mutations to designed combinatorial mutants are unpredictable. Screening designed mutations that affect enzyme catalytic activity enables evolutions towards efficient activities. Here, Bacillus subtilis LipA (BSLA) was selected as a model protein for thermostabilization designs, and the circular dichroism measurements showed six combinatorial designs with improved stability (from 5.81 degrees C to 13.61 degrees C). Based on molecular dynamic simulations, the conformational dynamics of the mutants revealed that mutations alter the populations of conformational states and the increased ensembles of inactive conformations might lead to a reduction in activity. We further demonstrated that the mutations responsible for the reduced enzyme catalytic activity involved a short dynamic correlation path to disturbing the equilibrium conformation of active sites. By removing N82V, which had a close dynamic correlation to the active sites in mutant D3, the redesigned mutant RD3 had an increased activity of 57.6%. By combining computational simulation with experimental verification, this work established that essential sites to counteract the activitystability trade-off in multipoint combinatorial mutants could be computationally predicted and thus provide a possible strategy by which to indirectly or directly guide protein design.
引用
收藏
页数:13
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