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RNA. 2018 Sep;24(9):1183-1194. doi: 10.1261/rna.065896.118. Epub 2018 Jun 21.

Assessing the performance of MM/PBSA and MM/GBSA methods. 8. Predicting binding free energies and poses of protein-RNA complexes.

Chen F1,2,3, Sun H1, Wang J4, Zhu F1, Liu H1, Wang Z1,2, Lei T1, Li Y5, Hou T1,2.

Author information

1
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
2
State Key Lab of CAD&CG, Zhejiang University, Hangzhou, Zhejiang 310058, China.
3
College of Life and Environmental Sciences, Shanghai Normal University, Shanghai 200234, China.
4
Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA.
5
Institute of Functional Nano and Soft Materials (FUNSOM), Soochow University, Suzhou, Jiangsu 215123, China.

Abstract

Molecular docking provides a computationally efficient way to predict the atomic structural details of protein-RNA interactions (PRI), but accurate prediction of the three-dimensional structures and binding affinities for PRI is still notoriously difficult, partly due to the unreliability of the existing scoring functions for PRI. MM/PBSA and MM/GBSA are more theoretically rigorous than most scoring functions for protein-RNA docking, but their prediction performance for protein-RNA systems remains unclear. Here, we systemically evaluated the capability of MM/PBSA and MM/GBSA to predict the binding affinities and recognize the near-native binding structures for protein-RNA systems with different solvent models and interior dielectric constants (εin). For predicting the binding affinities, the predictions given by MM/GBSA based on the minimized structures in explicit solvent and the GBGBn1 model with εin = 2 yielded the highest correlation with the experimental data. Moreover, the MM/GBSA calculations based on the minimized structures in implicit solvent and the GBGBn1 model distinguished the near-native binding structures within the top 10 decoys for 117 out of the 148 protein-RNA systems (79.1%). This performance is better than all docking scoring functions studied here. Therefore, the MM/GBSA rescoring is an efficient way to improve the prediction capability of scoring functions for protein-RNA systems.

KEYWORDS:

MM/GBSA; MM/PBSA; binding free energy; docking; protein–RNA interactions

PMID:
29930024
PMCID:
PMC6097651
DOI:
10.1261/rna.065896.118
[Indexed for MEDLINE]
Free PMC Article

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