Molecular Dynamics Simulations of Transmembrane Cyclic Peptide Nanotubes Using Classical Force Fields, Hydrogen Mass Repartitioning, and Hydrogen Isotope Exchange Methods: A Critical Comparison

Abstract

Self-assembled cyclic peptide nanotubes with alternating D- and L-amino acid residues in the sequence of each subunit have attracted a great deal of attention due to their potential for new nanotechnology and biomedical applications, mainly in the field of antimicrobial peptides. Molecular dynamics simulations can be used to characterize these systems with atomic resolution at different time scales, providing information that is difficult to obtain via wet lab experiments. However, the performance of classical force fields typically employed in the simulation of biomolecules has not yet been extensively tested with this kind of highly constrained peptide. Four different classical force fields (AMBER, CHARMM, OPLS, and GROMOS), using a nanotube formed by eight D,L-α-cyclic peptides inserted into a lipid bilayer as a model system, were employed here to fill this gap. Significant differences in the pseudo-cylindrical cavities formed by the nanotubes were observed, the most important being the diameter of the nanopores, the number and location of confined water molecules, and the density distribution of the solvent molecules. Furthermore, several modifications were performed on GROMOS54a7, aiming to explore acceleration strategies of the MD simulations. The hydrogen mass repartitioning (HMR) and hydrogen isotope exchange (HIE) methods were tested to slow down the fastest degrees of freedom. These approaches allowed a significant increase in the time step employed in the equation of the motion integration algorithm, from 2 fs up to 5–7 fs, with no serious changes in the structural and dynamical properties of the nanopores. Subtle differences with respect to the simulations with the unmodified force fields were observed in the concerted movements of the cyclic peptides, as well as in the lifetime of several H-bonds. All together, these results are expected to contribute to better understanding of the behavior of self-assembled cyclic peptide nanotubes, as well as to support the methods tested to speed up general MD simulations; additionally, they do provide a number of quantitative descriptors that are expected to be used as a reference to design new experiments intended to validate and complement computational studies of antimicrobial cyclic peptides.

Therapeutic peptides for coronary artery diseases: in silico methods and current perspectives

“…Molecular dynamics simulations methods, which enable the simulation of all atoms of biomolecules, provide advanced methods for the comprehensive analysis of peptide interactions and stability. Force fields such as AMBER (Ponder and Case 2003 ), CHARMM (Vanommeslaeghe et al 2010 ), GROMOS (Schmid et al 2011 ), and OPLS (Jorgensen et al 1996 ) which can be used in MD simulations, affect the efficacy of MD results by varying the calculation of peptide and condition specific forces (Jephthah et al 2021 ; Man et al 2019 ; Conde et al 2022 ). Molecular dynamics simulations are critical for demonstrating the experimental potential of peptides developed for therapeutic purposes, as simulation packages such as AMBER (Salomon-Ferrer et al 2013 ), GROMACS (Abraham et al 2015 ), CHARMM (Brooks et al 2009 ) and NAMD (Phillips et al 2005 ) can be used to comprehensively analyze interactions and stability.…”

Identifying Key Binding Interactions Between the Cardiac L-Type Calcium Channel and Calmodulin Using Molecular Dynamics Simulations

“…For all ions, we used the Li Merz 12−6−4 ion parameters with the C4 correction term applied using parmed. 40,41 To extend the simulation length, we employed hydrogen mass repartitioning (HMR) 42 to all of our model systems. This change allowed us to increase the time step in our simulations from 0.002 to 0.004 ps, which in turn increased our total simulation run time for each replica to 2 μs.…”

CYCLOPEp Builder: Facilitating cyclic peptide and nanotube research through a user-friendly web platform

“…The inception of SCPNs can be traced back to theoretical musings in 1974 [6] , with the first synthetic steps taken in 1993 [7] , employing alternating D , L -α-CPs to yield structures with significant potential as biomimetic transport systems or antimicrobial agents. However, studying the self-assembly of CPs into SCPNs has been limited by experimental constraints, propelling Molecular Dynamics (MD) simulations to the forefront [8] , [9] , [10] , [11] , [12] , [13] , [14] . MD simulations serve as a powerful tool to explore the self-assembly and dynamic behavior of SCPNs, providing valuable insights that are beyond the reach of direct experimental techniques.…”