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The Kink-Turn 7 Motif: An Additional Test for RNA Force Field Performance
Toon Lemmens1,2, Vojtěch Mlýnský1, Jiří Šponer1,3
1Institute of Biophysics of the Czech Academy of Sciences, Královopolská 135, Brno 612 00, Czech Republic.
Journal of Chemical Theory and Computation
|December 8, 2025
Summary
RNA force fields (FFs) struggle to accurately simulate the kink-turn motif. While OL3 and AMOEBA FFs perform best, newer variants show limitations, highlighting the need for kink-turn inclusion in FF development.
Area of Science:
- Biophysics
- Computational Biology
- Structural Biology
Background:
- The kink-turn is a crucial RNA structural motif forming a sharp bend in the A-form helix.
- Its complex noncanonical interactions (sheared AG pairs, A-minor, base-sugar) challenge molecular dynamics simulations.
- Accurate force fields (FFs) are essential for simulating RNA structures and dynamics.
Purpose of the Study:
- To evaluate the performance of various contemporary RNA force fields in simulating the ribosomal kink-turn 7 (Kt-7) motif.
- To identify FFs that accurately capture the structural features of the kink-turn.
- To assess the suitability of FFs for simulating larger RNA systems containing kink-turns.
Main Methods:
- Extended molecular dynamics simulations of the ribosomal Kt-7 motif.
- Utilized a wide range of pair-additive and polarizable RNA force fields.
- Comparative analysis of simulated structures against known Kt-7 structural features.
Main Results:
- No single FF perfectly reproduced all Kt-7 structural features.
- The OL3 and polarizable AMOEBA FFs demonstrated the best overall performance.
- Some newer FFs exhibited difficulties with the tertiary A-minor interaction and showed irreversible unkinking.
- FF performance varied significantly, indicating sensitivity to parametrization.
Conclusions:
- The kink-turn motif is a sensitive test for RNA force field accuracy.
- OL3 and AMOEBA are recommended for simulations involving kink-turns.
- Concerns exist regarding the over-parametrization of some newer FFs for small systems.
- Kink-turn structures should be incorporated into FF training and benchmarking datasets to improve robustness.
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