Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates

PLoS Comput Biol. 2025 Jan 13;21(1):e1012737. doi: 10.1371/journal.pcbi.1012737. eCollection 2025 Jan.

Abstract

Intracellular liquid-liquid phase separation (LLPS) of proteins and nucleic acids is a fundamental mechanism by which cells compartmentalize their components and perform essential biological functions. Molecular simulations play a crucial role in providing microscopic insights into the physicochemical processes driving this phenomenon. In this study, we systematically compare six state-of-the-art sequence-dependent residue-resolution models to evaluate their performance in reproducing the phase behaviour and material properties of condensates formed by seven variants of the low-complexity domain (LCD) of the hnRNPA1 protein (A1-LCD)-a protein implicated in the pathological liquid-to-solid transition of stress granules. Specifically, we assess the HPS, HPS-cation-π, HPS-Urry, CALVADOS2, Mpipi, and Mpipi-Recharged models in their predictions of the condensate saturation concentration, critical solution temperature, and condensate viscosity of the A1-LCD variants. Our analyses demonstrate that, among the tested models, Mpipi, Mpipi-Recharged, and CALVADOS2 provide accurate descriptions of the critical solution temperatures and saturation concentrations for the multiple A1-LCD variants tested. Regarding the prediction of material properties for condensates of A1-LCD and its variants, Mpipi-Recharged stands out as the most reliable model. Overall, this study benchmarks a range of residue-resolution coarse-grained models for the study of the thermodynamic stability and material properties of condensates and establishes a direct link between their performance and the ranking of intermolecular interactions these models consider.

MeSH terms

  • Benchmarking
  • Biomolecular Condensates* / chemistry
  • Computational Biology
  • Heterogeneous Nuclear Ribonucleoprotein A1 / chemistry
  • Humans
  • Molecular Dynamics Simulation*
  • Phase Transition
  • Proteins* / chemistry
  • Viscosity

Substances

  • Heterogeneous Nuclear Ribonucleoprotein A1
  • Proteins

Grants and funding

A. F. acknowledges funding from the Ramon y Cajal fellowship (RYC2021- 030937-I) and Spanish National Grant (PID2022-136919NA-C33) I. S.-B. acknowledges funding from the Derek Brewer scholarship of Emmanuel College and EPSRC Doctoral Training Programme studentship, number EP/T517847/1. R.C.-G. acknowledges funding from the European Research Council (ERC) under the European Union Horizon 2020 research and innovation programme (grant agreement 803326). A. T. is funded by European Research Council (ERC) under the European Union Horizon 2020 research and innovation programme (grant agreement 803326) and Ramon y Cajal fellowship (RYC2021-030937-I). J. R. E. also acknowledges funding from the Roger Ekins Research Fellowship of Emmanuel College, the Ramon y Cajal fellowship (RYC2021-030937-I) and the Spanish National Agency for Research (PID2022-136919NA-C33). A.R also acknowledges funding from PID2023-147156NB-I00 of the Spanish Ministry for Science, Innovation and Universities. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.