Accelerating the Ensemble Convergence of RNA Hairpin Simulations with a Replica Exchange Structure Reservoir.
Accelerating the Ensemble Convergence of RNA Hairpin Simulations with a Replica Exchange Structure Reservoir.
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DOI：
10.1021/acs.jctc.2c00065
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发表时间：
2022-05
影响因子：
5.5
通讯作者：
Kenneth Lam;Koushik Kasavajhala;Sarah Gunasekera;Carlos Simmerling
中科院分区：
文献类型：
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作者：
Kenneth Lam;Koushik Kasavajhala;Sarah Gunasekera;Carlos Simmerling
RNA是许多生物过程的关键参与者，但使用计算机模拟的RNA研究落后于蛋白质，主要是由于不发达的力场和RNA的缓慢动力学。为力场开发和其他研究生成收敛的RNA集合仍然是一个挑战。在这项研究中，我们探讨了复制交换分子动力学的能力，以获得收敛良好的构象合奏两RNA发夹系统在一个隐含的溶剂。即使对于这些小的模型系统，标准的REMD仍然计算成本高，但耦合到一个预先生成的结构库使用水库REMD方法提供了一个显着的加速集合收敛的两个模型系统。这种精确的系综可以促进RNA力场的开发和验证，并将模拟应用于更复杂的RNA系统。详细研究了将R-REMD应用于RNA的优点和剩余挑战。
RNA is a key participant in many biological processes, but studies of RNA using computer simulations lag behind those of proteins, largely due to less-developed force fields and the slow dynamics of RNA. Generating converged RNA ensembles for force field development and other studies remains a challenge. In this study, we explore the ability of replica exchange molecular dynamics to obtain well-converged conformational ensembles for two RNA hairpin systems in an implicit solvent. Even for these small model systems, standard REMD remains computationally costly, but coupling to a pre-generated structure library using the reservoir REMD approach provides a dramatic acceleration of ensemble convergence for both model systems. Such precise ensembles could facilitate RNA force field development and validation and applications of simulation to more complex RNA systems. The advantages and remaining challenges of applying R-REMD to RNA are investigated in detail.