Chemically Informed Coarse-Graining of Electrostatic Forces in Charge-Rich Biomolecular Condensates

ACS Central Science, Journal Year: 2025, Volume and Issue: 11(2), P. 302 - 321

Published: Feb. 11, 2025

Biomolecular condensates composed of highly charged biomolecules, such as DNA, RNA, chromatin, and nucleic-acid binding proteins, are ubiquitous in the cell nucleus. The biophysical properties these charge-rich largely regulated by electrostatic interactions. Residue-resolution coarse-grained models that describe solvent ions implicitly widely used to gain mechanistic insights into condensates, offering transferability, computational efficiency, accurate predictions for multiple systems. However, their predictive accuracy diminishes due implicit treatment ions. Here, we present Mpipi-Recharged, a residue-resolution model improves description charge effects biomolecular containing disordered multidomain and/or single-stranded RNAs. Mpipi-Recharged introduces pair-specific asymmetric Yukawa potential, informed atomistic simulations. We show this coarse-graining forces captures intricate effects, blockiness, stoichiometry variations complex coacervates, modulation salt concentration, without requiring explicit solvation. provides excellent agreement with experiments predicting phase behavior condensates. Overall, tools available investigate physicochemical mechanisms regulating enhancing scope computer simulations field.

Language: Английский

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

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(1), P. e1012737 - e1012737

Published: Jan. 13, 2025

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

Language: Английский

Toward Predictive Coarse-Grained Simulations of Biomolecular Condensates

Biochemistry, Journal Year: 2025, Volume and Issue: unknown

Published: April 2, 2025

Phase separation is a fundamental process that enables cellular organization by forming biomolecular condensates. These assemblies regulate diverse functions creating distinct environments, influencing reaction kinetics, and facilitating processes such as genome organization, signal transduction, RNA metabolism. Recent studies highlight the complexity of condensate properties, shaped intrinsic molecular features external factors temperature pH. Molecular simulations serve an effective approach to establishing comprehensive framework for analyzing these influences, offering high-resolution insights into stability, dynamics, material properties. This review evaluates recent advancements in simulations, with particular focus on coarse-grained 1-bead-per-amino-acid (1BPA) protein models, emphasizes OpenABC, tool designed simplify streamline simulations. OpenABC supports implementation various force fields, enabling their performance evaluation. Our benchmarking identifies inconsistencies phase behavior predictions across even though models accurately capture single-chain statistics. finding underscores need enhanced field accuracy, achievable through enriched training data sets, many-body potentials, advanced optimization techniques. Such refinements could significantly improve predictive capacity bridging details emergent behaviors.

Language: Английский