Simulating Polyproline II-Helix-Rich Peptides with the Latest Kirkwood–Buff Force Field: A Direct Comparison with AMBER and CHARMM

Abstract

We simulated the dynamics of a set of peptides characterized by ensembles rich in PPII-helical content, to assess the ability of the most recent Kirkwood−Buff force field (KBFF20) to sample this conformational peculiarity. KBFF has been previously shown to capably reproduce experimental dimensions of disordered proteins, while being limited in confidently sampling structured proteins. Further development of the force field bridged this gap. It is however still unknown what are the main differences between KBFF and AMBER/CHARMM force fields. A direct comparison is now possible as both AMBER/CHARMM force fields have been used to sample peptides rich in PPII-helical content. We found that KBFF20 samples' PPII-helical content qualitatively matches both AMBER and CHARMM force fields, with the main difference being the KBFF ability to populate the α R region of the Ramachandran plot in the set of simulated peptides. Overall, KBFF20 is a well-balanced force field, able to sample the dynamics of both structured and unstructured proteins.

Comparative molecular dynamics simulations of pathogenic and non-pathogenic huntingtin protein monomers and dimers

“…The PPII-helix structures were determined based on the dihedral angles of the protein backbone, ϕ and ψ, which fall into the range of −104 ≤ ϕ ≤ −46 and 116 ≤ ψ ≤ 174 for a PPII helix (Mansiaux et al, 2011;Yu et al, 2021). Previous studies have demonstrated that the assignment of the PPII helix using either DSSP-PPII or the backbone dihedral-angles approach provide highly similar results (Jephthah et al, 2021;McIvor et al, 2022). Conformational clustering of the trajectories was accomplished using the algorithm by Daura et al (Daura et al, 1999), which is a nearest neighbor algorithm, using the root mean square deviation (RMSD) between all trajectory snapshots together with an RMSD cutoff of 0.5 nm to assign the neighbors.…”