Allosteric regulatory control in dihydrofolate reductase is revealed by dynamic asymmetry
Allosteric regulatory control in dihydrofolate reductase is revealed by dynamic asymmetry
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DOI：
10.1002/pro.4700
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发表时间：
2023-06
期刊：
影响因子：
8
通讯作者：
I. C. Kazan;J. Mills;S. Ozkan
中科院分区：
文献类型：
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作者：
I. C. Kazan;J. Mills;S. Ozkan
我们用计算方法研究了大肠杆菌二氢叶酸还原酶（DHFR）突变与动力学之间的关系。我们的研究主要集中在M20和FG环上，它们在功能上很重要，并且受远端突变的影响。我们利用分子动力学模拟和位置特异性指标，包括动态柔韧性指数（DFI）和动态耦合指数（DCI），来分析野生型DHFR的动态，并将我们的结果与现有的深度突变扫描数据进行比较。我们的分析显示，DFI与DHFR位置的突变耐受性之间存在统计学上显著的关联，表明DFI可以预测功能上有益或有害的替代。我们还将不对称版本的DCI度量（DCIasym）应用于DHFR，发现某些远端残基控制M20和FG环的动力学，而其他残基则由它们控制。我们的DCIasym度量建议控制M20和FG环的残基在进化上是非保守的；这些位点的突变可以增强酶的活性。另一方面，由环控制的残基在突变时大多对功能有害，并且也是进化保守的。我们的研究结果表明，基于动态的指标可以识别解释突变和蛋白质功能之间关系的残基，或者可以靶向合理地设计具有增强活性的酶。
We investigated the relationship between mutations and dynamics in Escherichia coli dihydrofolate reductase (DHFR) using computational methods. Our study focused on the M20 and FG loops, which are known to be functionally important and affected by mutations distal to the loops. We used molecular dynamics simulations and developed position‐specific metrics, including the dynamic flexibility index (DFI) and dynamic coupling index (DCI), to analyze the dynamics of wild‐type DHFR and compared our results with existing deep mutational scanning data. Our analysis showed a statistically significant association between DFI and mutational tolerance of the DHFR positions, indicating that DFI can predict functionally beneficial or detrimental substitutions. We also applied an asymmetric version of our DCI metric (DCIasym) to DHFR and found that certain distal residues control the dynamics of the M20 and FG loops, whereas others are controlled by them. Residues that are suggested to control the M20 and FG loops by our DCIasym metric are evolutionarily nonconserved; mutations at these sites can enhance enzyme activity. On the other hand, residues controlled by the loops are mostly deleterious to function when mutated and are also evolutionary conserved. Our results suggest that dynamics‐based metrics can identify residues that explain the relationship between mutation and protein function or can be targeted to rationally engineer enzymes with enhanced activity.