Accelerated Simulations Reveal Physicochemical Factors Governing Stability and Composition of RNA Clusters

Area of Science:

• Biophysics
• Computational Biology
• Molecular Biology

Background:

• RNA repeat sequences can undergo phase separation into protein-free biomolecular condensates.
• These RNA repeat sequences are linked to neurological disorders like Huntington's disease.
• Characterizing RNA phase behavior at submolecular resolution remains a challenge.

Purpose of the Study:

• To develop and utilize a residue-resolution coarse-grained model for studying protein-free RNA systems.
• To investigate the clustering propensities of all 20 nonredundant trinucleotide repeat sequences.
• To uncover physicochemical principles governing RNA cluster formation, stability, and composition.

Main Methods:

• Implementation of a residue-resolution coarse-grained model in LAMMPS, incorporating RNA sequence and structure.
• Achieving a multifold speedup in simulation time compared to previous methods.
• Systematic analysis of clustering propensities for various RNA repeat sequences, including trinucleotide and quadranucleotide repeats.

Main Results:

• Model results align with experimental findings, highlighting the roles of canonical base-pairing and G-U wobble pairs in RNA cluster formation.
• Strong entropic contributions to the stability and composition of RNA clusters were identified in both single-component and binary mixtures.
• Odd trinucleotide repeats show stronger clustering tendencies than even quadranucleotide repeats due to differences in consecutive base pair arrangements.

Conclusions:

• The study provides an efficient computational tool for probing RNA cluster formation at submolecular resolution.
• Physicochemical principles governing the stability and composition of RNA clusters have been elucidated.
• Findings contribute to understanding the role of RNA phase separation in health and disease, particularly in neurological disorders.