Temperature-Dependent Coarse-Grained Model for Simulations of Intrinsically Disordered Protein LCST and UCST Liquid–Liquid Phase Separations

Many intrinsically disordered proteins (IDPs) can undergo a liquid-liquid phase separation (LLPS) in water, depending on solution conditions (temperature, pH, and ionic strength). There are two types of LLPS that are controlled by temperature: those occurring above a lower critical solution temperature (LCST) and those occurring below an upper critical solution temperature (UCST). IDP coarse-grained (CG) models are particularly appropriate for investigating the physical and chemical factors that govern their LLPS and supramolecular organization. However, the development of CG models allowing simulations of both LCST and UCST behavior of temperature-sensitive IDPs is still in its infancy. In this context, we present here a novel temperature-dependent (TD) CG model for IDP simulations based on the MARTINI 3 force field. The model was developed by modifying the Lennard-Jones potentials between apolar or charged solute beads and water with a TD rescaling factor. It was parametrized to fit the TD potentials of mean force (PMF) between two apolar or two charged molecules computed using all-atom (AA) simulations. We show that the TD CG model is able to reproduce the experimentally known LLPS of both LCST and UCST low-complexity sequences and to estimate phase transition temperatures comparable to experimental measurements.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-04-25
DOI
https://doi.org/10.1021/acs.jctc.5c00212
Citations
2
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
1.61

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Temperature-Dependent Coarse-Grained Model for Simulations of Intrinsically Disordered Protein LCST and UCST Liquid–Liquid Phase Separations

Yingmin Jiang, Tâp Ha‐Duong
2 citations
Journal of Chemical Theory and Computation
Protein Structure and Dynamics
1.61
article

Temperature-Dependent Coarse-Grained Model for Simulations of Intrinsically Disordered Protein LCST and UCST Liquid–Liquid Phase Separations

Yingmin Jiang, Tâp Ha‐Duong
article en
2 citations

Abstract

Many intrinsically disordered proteins (IDPs) can undergo a liquid-liquid phase separation (LLPS) in water, depending on solution conditions (temperature, pH, and ionic strength). There are two types of LLPS that are controlled by temperature: those occurring above a lower critical solution temperature (LCST) and those occurring below an upper critical solution temperature (UCST). IDP coarse-grained (CG) models are particularly appropriate for investigating the physical and chemical factors that govern their LLPS and supramolecular organization. However, the development of CG models allowing simulations of both LCST and UCST behavior of temperature-sensitive IDPs is still in its infancy. In this context, we present here a novel temperature-dependent (TD) CG model for IDP simulations based on the MARTINI 3 force field. The model was developed by modifying the Lennard-Jones potentials between apolar or charged solute beads and water with a TD rescaling factor. It was parametrized to fit the TD potentials of mean force (PMF) between two apolar or two charged molecules computed using all-atom (AA) simulations. We show that the TD CG model is able to reproduce the experimentally known LLPS of both LCST and UCST low-complexity sequences and to estimate phase transition temperatures comparable to experimental measurements.

Journal of Chemical Theory and ComputationVol. 21(9)
Université Paris-Saclay (FR)
China Scholarship Council, Grand Équipement National De Calcul Intensif
Zero hunger
Openalex Percentile: Top 18%
Protein Structure and Dynamics
1.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.