Effects and limitations of a nucleobase-driven backmapping procedure for nucleic acids using steered molecular...

Area of Science:

• Computational Biology
• Biophysics
• Structural Biology

Background:

• Coarse-grained models enhance nucleic acid structure prediction efficiency.
• These models identify key degrees of freedom and interactions for structure description.
• An all-atom representation in explicit solvent is desired for coarse-grained predictions.

Purpose of the Study:

• To provide an all-atom representation for the SPlit and conQueR (SPQR) coarse-grained RNA model.
• To introduce and evaluate a backmapping procedure using steered molecular dynamics.
• To analyze the impact of backmapping on interaction networks and backbone conformations.

Main Methods:

• Developed a backmapping procedure to convert coarse-grained predictions to atomistic structures.
• Utilized steered molecular dynamics to enforce predicted structures into atomistic representations.
• Minimized the ERMSD (Edgewise Root Mean Square Deviation) between atomistic and target structures.

Main Results:

• The backmapping procedure reliably recovers the geometry of target native RNA structures.
• Limitations were observed in regions with unpaired bases, such as bulges.
• Folding pathways can be altered based on ERMSD parameters and alternative metrics (e.g., RMSD).

Conclusions:

• The SPQR coarse-grained model's backmapping procedure effectively generates accurate all-atom RNA structures.
• The method shows promise for RNA structure prediction, though refinement is needed for specific regions.
• Parameter choices in metrics like ERMSD significantly influence the predicted folding pathways.