Quantum chemical benchmark study on 46 RNA backbone families using a dinucleotide unit

Area of Science:

• Computational chemistry
• Biophysics
• Structural biology

Background:

• Accurate prediction of RNA structure and energy is crucial for understanding its biological functions.
• Existing computational methods, including force fields, have limitations in describing RNA conformational landscapes.
• A comprehensive benchmark dataset is needed to evaluate and develop new computational approaches.

Purpose of the Study:

• To create a benchmark dataset (UpU46) of quantum chemical structure-energy data for uracil dinucleotides (UpU).
• To evaluate the performance of various quantum chemical methods, including dispersion-corrected DFT and double-hybrid functionals, for RNA conformational energies.
• To compare the accuracy of these methods against the Amber RNA bsc0χOL3 force field.

Main Methods:

• Generation of the UpU46 benchmark set comprising 46 uracil dinucleotides representing all known RNA backbone conformational families.
• Utilized penalty-function-based restrained optimizations with COSMO TPSS-D3/def2-TZVP for geometry relaxation.
• Employed high-level wave function methods (DLPNO-CCSD(T)) as a reference and a range of DFT methods (e.g., DFT-D3, VV10, M06-2X) to calculate conformational energies.

Main Results:

• Most dispersion-corrected DFT methods significantly outperformed the Amber RNA force field, achieving mean absolute deviations (MADs) of ~0.4-0.6 kcal/mol.
• Double-hybrid density functionals demonstrated the highest accuracy among the tested DFT methods.
• Low-cost quantum chemical methods (e.g., PM6-D3H+, HF-3c) struggled to achieve satisfactory accuracy for UpU conformational energies.

Conclusions:

• The UpU46 benchmark dataset provides a valuable resource for assessing and developing accurate computational methods for nucleic acids.
• Dispersion-corrected DFT methods offer a significant improvement over traditional force fields for RNA conformational energy calculations.
• Further development is needed for low-cost quantum chemical methods to accurately capture RNA conformational energetics.