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Benchmarking Adaptive Steered Molecular Dynamics (ASMD) on CHARMM Force Fields.

Caley Allen¹, Hailey R Bureau¹, T Dwight McGee²

¹Department of Chemistry, Johns Hopkins University, Baltimore, MD, 21218.

Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry

|May 20, 2022

Summary

This summary is machine-generated.

Adaptive steered molecular dynamics (ASMD) simulations reveal that the CHARMM c36 force field offers the most robust results for calculating peptide unfolding potentials of mean force (PMFs). This finding is crucial for accurate molecular dynamics simulations.

Keywords:

Adaptive Steered Molecular Dynamics CHARMM Jarzynski's Equality Peptide Structure

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Area of Science:

Computational chemistry
Molecular dynamics
Biophysics

Background:

Potentials of Mean Force (PMFs) are essential for understanding molecular interactions and conformational changes.
Accurate force fields are critical for reliable molecular dynamics (MD) simulations.

Purpose of the Study:

To benchmark the performance of different CHARMM force field versions (c22, c27, c36) in adaptive steered molecular dynamics (ASMD) simulations.
To determine the most robust force field for calculating PMFs during peptide unfolding.

Main Methods:

Utilized adaptive steered molecular dynamics (ASMD) to simulate the unfolding of two helical peptides ( and 1PEF).
Compared results obtained using three popular CHARMM force field versions: c22, c27, and c36.
Analyzed the potentials of mean force (PMFs) along the end-to-end distance during forced unfolding.

Main Results:

The choice of force field significantly impacts the calculated PMFs.
CHARMM c36 demonstrated superior robustness and reliability in forced unfolding simulations compared to c22 and c27.
Qualitative and quantitative differences were observed across the CHARMM force field versions.

Conclusions:

The CHARMM c36 force field is recommended for ASMD simulations requiring accurate PMF calculations of peptide unfolding.
Force field selection is a critical parameter influencing the outcomes of molecular dynamics simulations.