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利用局部蛋白模型质量评估来指导基于分子动力学的精修策略。

Using Local Protein Model Quality Estimates to Guide a Molecular Dynamics-Based Refinement Strategy.

机构信息

School of Biological Sciences, University of Reading, Reading, UK.

出版信息

Methods Mol Biol. 2023;2627:119-140. doi: 10.1007/978-1-0716-2974-1_7.

Abstract

The refinement of predicted 3D models aims to bring them closer to the native structure by fixing errors including unusual bonds and torsion angles and irregular hydrogen bonding patterns. Refinement approaches based on molecular dynamics (MD) simulations using different types of restraints have performed well since CASP10. ReFOLD, developed by the McGuffin group, was one of the many MD-based refinement approaches, which were tested in CASP 12. When the performance of the ReFOLD method in CASP12 was evaluated, it was observed that ReFOLD suffered from the absence of a reliable guidance mechanism to reach consistent improvement for the quality of predicted 3D models, particularly in the case of template-based modelling (TBM) targets. Therefore, here we propose to utilize the local quality assessment score produced by ModFOLD6 to guide the MD-based refinement approach to further increase the accuracy of the predicted 3D models. The relative performance of the new local quality assessment guided MD-based refinement protocol and the original MD-based protocol ReFOLD are compared utilizing many different official scoring methods. By using the per-residue accuracy (or local quality) score to guide the refinement process, we are able to prevent the refined models from undesired structural deviations, thereby leading to more consistent improvements. This chapter will include a detailed analysis of the performance of the local quality assessment guided MD-based protocol versus that deployed in the original ReFOLD method.

摘要

预测三维模型的精修旨在通过修正包括异常键和扭转角以及不规则氢键模式等错误,使其更接近天然结构。自 CASP10 以来,使用不同类型约束的基于分子动力学 (MD) 模拟的精修方法表现良好。由 McGuffin 小组开发的 ReFOLD 是众多基于 MD 的精修方法之一,在 CASP 12 中进行了测试。当评估 ReFOLD 方法在 CASP12 中的性能时,观察到 ReFOLD 缺乏可靠的指导机制来持续提高预测三维模型的质量,特别是在基于模板建模 (TBM) 目标的情况下。因此,在这里我们提议利用 ModFOLD6 生成的局部质量评估分数来指导基于 MD 的精修方法,以进一步提高预测三维模型的准确性。利用许多不同的官方评分方法比较了新的局部质量评估指导的基于 MD 的精修协议和原始的基于 MD 的协议 ReFOLD 的相对性能。通过使用残基精度(或局部质量)分数来指导精修过程,我们能够防止精修模型发生不必要的结构偏差,从而实现更一致的改进。这一章将包括对局部质量评估指导的基于 MD 的协议与原始 ReFOLD 方法中部署的协议的性能进行详细分析。

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