How Well Do Molecular Dynamics Force Fields Model Peptides: A Systematic Benchmark across Diverse Folding Behaviors

Area of Science:

• Computational chemistry
• Molecular dynamics simulations
• Biophysics

Background:

• Linear peptides are crucial in biology and drug discovery, often mediating protein-protein interactions.
• Peptide structural plasticity presents significant challenges for accurate molecular simulations.
• Fixed-charge force fields are widely used but their performance with peptides is not well-established.

Purpose of the Study:

• To benchmark the performance of 11 fixed-charge force fields for simulating diverse peptide systems.
• To assess force field biases, stability, and folding behavior across structured, context-sensitive, and disordered peptides.
• To provide practical guidance for peptide molecular modeling and inform future force field development.

Main Methods:

• Benchmarking 11 popular and emerging fixed-charge force fields.
• Simulating 12 curated peptides, including structured miniproteins, epitopes, and disordered sequences.
• Running simulations from both folded (200 ns) and extended (10 μs) states for each peptide.

Main Results:

• Consistent trends observed across force fields, with some showing strong structural bias and others allowing reversible fluctuations.
• No single force field demonstrated optimal performance across all tested peptide systems.
• Identified limitations in current force fields' ability to balance peptide disorder and secondary structure, especially in conformational selection.

Conclusions:

• Current fixed-charge force fields exhibit limitations in accurately modeling the conformational landscape of diverse peptides.
• The study provides a benchmark framework for evaluating and developing peptide-specific force fields.
• Findings offer practical insights for researchers performing molecular simulations of peptides in drug discovery and biological studies.