论文标题

自动学习琥珀RNA力场中的氢键固定

Automatic learning of hydrogen-bond fixes in an AMBER RNA force field

论文作者

Fröhlking, Thorben, Mlýnský, Vojtěch, Janeček, Michal, Kührová, Petra, Krepl, Miroslav, Banáš, Pavel, Šponer, Jiří, Bussi, Giovanni

论文摘要

当前力场再现RNA结构动力学的能力是有限的。已经开发了几种利用实验数据以实现实验一致的方法。我们在此扩展了一个现有的框架,该框架允许任意选择的力场校正项,可以通过量化可观察到的模拟和相应实验的可观察结果之间的差异来拟合。我们采用强大的正则化协议来避免过度拟合,并介绍和比较许多不同的正则化策略,即L1-,L2-,Kish尺寸,相对Kish尺寸和相对熵 - 和相对熵 - 元素。培训组包括GACC四聚体以及更具挑战性的系统,即GCGAGAGC和GCUUCGGC RNA traloops。用自动确定的参数校正了琥珀RNA力场中的特定分子内氢键,我们称为GHBFIX $ _ {opt} $。涉及对训练集(GCUUCGGC)中存在的系统的单独模拟的验证和在训练期间未见的新系统(CAAU和UUUU TERMERS)在使用新参数时显示了针对四边形本地群体的改进,以及与Tetramers的NMR-experiments的一致性。然后,我们模拟折叠的RNA(扭结和L1茎rRNA),其中包括训练组中不充分存在的氢键类型。这允许对名为GHBFIX21的参数集进行最终修改,并建议适用于更宽的RNA系统。

The capability of current force fields to reproduce RNA structural dynamics is limited. Several methods have been developed to take advantage of experimental data in order to enforce agreement with experiments. We herein extend an existing framework, which allows arbitrarily chosen force-field correction terms to be fitted by quantification of the discrepancy between observables back-calculated from simulation and corresponding experiments. We apply a robust regularization protocol to avoid overfitting, and additionally introduce and compare a number of different regularization strategies, namely L1-, L2-, Kish Size-, Relative Kish Size- and Relative Entropy-penalties. The training set includes a GACC tetramer as well as more challenging systems, namely gcGAGAgc and gcUUCGgc RNA tetraloops. Specific intramolecular hydrogen bonds in the AMBER RNA force field are corrected with automatically determined parameters that we call gHBfix$_{opt}$. A validation involving a separate simulation of a system present in the training set (gcUUCGgc) and new systems not seen during training (CAAU and UUUU tetramers) displays improvements regarding native population of the tetraloop as well as good agreement with NMR-experiments for tetramers when using the new parameters. Then we simulate folded RNAs (a kink-turn and L1 stalk rRNA) including hydrogen bond types not sufficiently present in the training set. This allows a final modification of the parameter set which is named gHBfix21 and is suggested to be applicable to a wider range of RNA systems.

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