Matching correlations matters: Modeling friction in a hydrophobic folding transition

The generalized Langevin equation provides a powerful framework for modeling and interpreting the conformational dynamics of (macro)molecules in solution. However, recent studies have shown that the standard fluctuation-dissipation relation-linking the memory kernel to the statistics of the random force-can include a non-zero cross correlation term between conservative and random forces. This raises questions about how to correctly extract memory kernels from simulation data when this correlation is neglected and whether inverting the Volterra equation to obtain a memory kernel yields a physically meaningful result. In a recent work [Wolf et al. J. Chem. Phys. 162, 054113 (2025)], we proposed an approximation to account for the cross correlation term. We demonstrate in this work that cross correlations play a significant role in the collapse transition of a hydrophobic polymer under various solvent conditions. In addition, we demonstrate that our proposed approximation yields an improved description of barrier crossing times. Notably, we find that this improvement has the same magnitude as the improvement gained by accounting for memory effects.

Authors

Institutions

Publication Details

Journal
The Journal of Chemical Physics
Published
2025-09-22
DOI
https://doi.org/10.1063/5.0289081
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Matching correlations matters: Modeling friction in a hydrophobic folding transition

Madhusmita Tripathy, Nico F. A. van der Vegt, Niklas Wolf
The Journal of Chemical Physics
Protein Structure and Dynamics
article

Matching correlations matters: Modeling friction in a hydrophobic folding transition

Madhusmita Tripathy, Nico F. A. van der Vegt, Niklas Wolf
article en

Abstract

The generalized Langevin equation provides a powerful framework for modeling and interpreting the conformational dynamics of (macro)molecules in solution. However, recent studies have shown that the standard fluctuation-dissipation relation-linking the memory kernel to the statistics of the random force-can include a non-zero cross correlation term between conservative and random forces. This raises questions about how to correctly extract memory kernels from simulation data when this correlation is neglected and whether inverting the Volterra equation to obtain a memory kernel yields a physically meaningful result. In a recent work [Wolf et al. J. Chem. Phys. 162, 054113 (2025)], we proposed an approximation to account for the cross correlation term. We demonstrate in this work that cross correlations play a significant role in the collapse transition of a hydrophobic polymer under various solvent conditions. In addition, we demonstrate that our proposed approximation yields an improved description of barrier crossing times. Notably, we find that this improvement has the same magnitude as the improvement gained by accounting for memory effects.

The Journal of Chemical PhysicsVol. 163(12)
Technische Universität Darmstadt (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 77%
Protein Structure and Dynamics
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.

Matching correlations matters: Modeling friction in a hydrophobic folding transition — Madhusmita Tripathy, Nico F. A. van der Vegt, et al. · The Journal of Chemical Physics (2025) | TGRS Research Map | TGRS