What is the best reference state for building statistical potentials in RNA 3D structure evaluation?
What is the best reference state for building statistical potentials in RNA 3D structure evaluation?
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在 RNA 3D 结构评估中构建统计势的最佳参考状态是什么？
DOI：
10.1261/rna.069872.118
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Tan Zhi-Jie
中科院分区：
文献类型：
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作者：
Tan Ya-Lan;Feng Chen-Jie;Jin Lei;Shi Ya-Zhou;Zhang Wenbing;Tan Zhi-Jie
基于知识的统计势已被证明是有效的蛋白质结构评估/预测，和各种统计势之间的核心差异归因于参考状态的选择。然而，对于RNA三维结构评估，仍然缺乏对参考状态的全面检查。在这项工作中，我们建立了六个统计势的基础上广泛使用的蛋白质结构评估的六个参考状态，包括平均，准化学近似，原子洗牌，有限理想气体，球形非相互作用，和随机行走链参考状态，我们检查了六个参考状态对三个RNA测试集，包括六个子集。我们广泛的研究表明，总体而言，对于识别原生结构和对诱饵结构进行排序，有限理想气体和随机行走链参考态略上级其他参考态，而对于识别近原生结构，这些参考态之间只有轻微的差异。我们进一步的分析表明，统计势函数的性能显然取决于训练集的质量。此外，我们发现统计势函数的性能与测试集的来源密切相关，对于三个真实测试子集，六种统计势函数的性能总体上都不理想。这项工作提出了一个全面的检查现有的参考状态和统计潜力的RNA三维结构评估。
Knowledge-based statistical potentials have been shown to be efficient in protein structure evaluation/prediction, and the core difference between various statistical potentials is attributed to the choice of reference states. However, for RNA 3D structure evaluation, a comprehensive examination on reference states is still lacking. In this work, we built six statistical potentials based on six reference states widely used in protein structure evaluation, including averaging, quasi-chemical approximation, atom-shuffled, finite-ideal-gas, spherical-noninteracting, and random-walk-chain reference states, and we examined the six reference states against three RNA test sets including six subsets. Our extensive examinations show that, overall, for identifying native structures and ranking decoy structures, the finite-ideal-gas and random-walk-chain reference states are slightly superior to others, while for identifying near-native structures, there is only a slight difference between these reference states. Our further analyses show that the performance of a statistical potential is apparently dependent on the quality of the training set. Furthermore, we found that the performance of a statistical potential is closely related to the origin of test sets, and for the three realistic test subsets, the six statistical potentials have overall unsatisfactory performance. This work presents a comprehensive examination on the existing reference states and statistical potentials for RNA 3D structure evaluation.