Comparison of Secondary Structure Formation Using 10 Different Force Fields in Microsecond Molecular Dynamics...

Area of Science:

• Biomolecular simulations
• Computational biophysics
• Protein folding

Background:

• Molecular dynamics (MD) simulations are crucial for understanding protein behavior.
• Different force fields and simulation parameters can significantly impact outcomes.
• Accurate prediction of peptide folding, like β-hairpin formation, is essential for biological insights.

Purpose of the Study:

• To compare the performance of 10 different biomolecular force fields in simulating the folding of a β-hairpin forming peptide derived from Nrf2.
• To evaluate the influence of charge groups, terminal capping, and phosphorylation on peptide folding.
• To provide guidance for selecting appropriate force fields in future molecular dynamics studies.

Main Methods:

• Conducted molecular dynamics (MD) simulations of a 16-mer Nrf2 β-hairpin peptide in explicit solvent.
• Utilized 10 distinct biomolecular force fields: Amber (ff99SB-ILDN, ff99SB*-ILDN, ff99SB, ff99SB*, ff03, ff03*), GROMOS96 (43a1p, 53a6), CHARMM27, and OPLS-AA/L.
• Performed simulations for at least 1 μs per replicate, totaling 37.2 μs, and examined effects of peptide modifications.

Main Results:

• Amber and GROMOS force fields (ff99SB-ILDN, ff99SB*-ILDN, ff99SB, ff99SB*, ff03, ff03*, 43a1p, 53a6) successfully predicted native-like β-hairpin structures at 310 K.
• CHARMM27 showed partial success in forming native hairpins at elevated temperatures.
• OPLS-AA/L failed to produce native hairpin structures across all tested temperatures.
• Phosphorylation of the β-turn threonine residue significantly altered hairpin formation.

Conclusions:

• The choice of biomolecular force field critically influences the accuracy of β-hairpin folding simulations.
• Amber and GROMOS force fields demonstrate greater reliability for this specific peptide system.
• This comprehensive comparison offers valuable insights for researchers selecting force fields for peptide and protein dynamics simulations.