Hierarchical Assembly of Single-Stranded RNA.

Area of Science:

• Structural biology
• Computational biophysics
• RNA biology

Background:

• Single-stranded RNA (ssRNA) is crucial for genetic information flow (e.g., mRNA) and biological regulation.
• The inherent flexibility of ssRNA poses significant challenges for experimental and computational structural determination.
• Accurate structural characterization of ssRNA is vital for understanding its diverse biological functions.

Purpose of the Study:

• To develop and validate a novel computational method for constructing accurate structural ensembles of single-stranded RNA (ssRNA).
• To assess the performance of the developed method against various experimental techniques.
• To demonstrate the method's applicability to complex RNA structures, including those with mixed base-pairing.

Main Methods:

• Hierarchical chain growth (HCG) was employed to assemble ssRNA structures from molecular dynamics (MD) simulation-derived fragment libraries.
• HCG was applied to both homo- and heteropolymeric ssRNA chains of varying lengths.
• Ensemble refinement using Bayesian inference (BioEn) was utilized to improve structural accuracy.

Main Results:

• HCG successfully generated structural ensembles for ssRNA that demonstrated good agreement with experimental data, including NMR, SAXS, and FRET.
• The method showed versatility by accurately modeling RNA structures containing both base-paired and base-unpaired regions.
• Refinement with BioEn further enhanced the concordance between computational models and experimental observations.

Conclusions:

• Hierarchical chain growth (HCG) provides a robust computational framework for characterizing the structural ensembles of dynamic single-stranded RNA molecules.
• The HCG method, augmented by Bayesian refinement, offers a powerful tool for integrating computational modeling with experimental data in RNA structural biology.
• This approach advances our ability to study RNA structures, including functionally important regions like the SARS-CoV-2 5' UTR.