Molecular dynamics simulation of the interactions between EHD1 EH domain and multiple peptides

Abstract

Abstract:Objective: To provide essential information for peptide inhibitor design, the interactions of Eps15 homology domain of Eps15 homology domain-containing protein 1 (EHD1 EH domain) with three peptides containing NPF (asparagine-proline-phenylalanine), DPF (aspartic acid-proline-phenylalanine), and GPF (glycine-proline-phenylalanine) motifs were deciphered at the atomic level. The binding affinities and the underlying structure basis were investigated. Methods: Molecular dynamics (MD) simulations were performed on EHD1 EH domain/peptide complexes for 60 ns using the GROMACS package. The binding free energies were calculated and decomposed by molecular mechanics/ generalized Born surface area (MM/GBSA) method using the AMBER package. The alanine scanning was performed to evaluate the binding hot spot residues using FoldX software. Results: The different binding affinities for the three peptides were affected dominantly by van der Waals interactions. Intermolecular hydrogen bonds provide the structural basis of contributions of van der Waals interactions of the flanking residues to the binding. Conclusions: van der Waals interactions should be the main consideration when we design peptide inhibitors of EHD1 EH domain with high affinities. The ability to form intermolecular hydrogen bonds with protein residues can be used as the factor for choosing the flanking residues.

Impact on S. aureus and E. coli membranes of treatment with chlorhexidine and alcohol solutions: insights from molecular simulations and nuclear magnetic resonance

“…The pressure of the system was maintained at 1 atm, with a time constant of 2 ps, using semi-isotropic pressure coupling with the Parrinello-Rahman [53,54] barostat. All van der Waals interactions were cut off at 1.2 nm and a smooth particle mesh Ewald [55] (PME) algorithm was used to treat electrostatic interactions with a real space cut off of 1.4 nm. Simulation parameters were chosen based on similar published studies of Piggot et al [34] For equilibration, each system was subjected to 500 ps of NVT simulation, followed by 2 ns of NPT.…”

A novel variant fibrinogen, AαE11del, demonstrating the importance of AαE11 residue in thrombin binding

“…The coupling algorithm of temperature (300 K) and pressure (1 bar) of each system was maintained using V-rescale (a modified Berendsen thermostat temperature coupling method) and the Parrinello-Rahman pressure coupling method, respectively, as described previously [22]. All bonds containing hydrogen atoms were constrained using the linear constraint solver algorithm, and the electrostatic interactions were treated with the particle-mesh-Ewald (PME) method, as described previously [23]. The stability of FpA fragment-thrombin complex models was analyzed using root-mean-square deviation (RMSD) (Figure S1), and snapshots in the MD simulation trajectory were confirmed using PyMOL [24].…”

Simulating Peptide Monolayer Formation: GnRH-I on Silica

“…Consequently, the simulations can be used to design effective technologies with optimal performance. For example, MD simulations can be used to study many biomedical-related issues such as drug resistance [ 1 ], drug development [ 2 ], effects of mutations in molecules [ 3 ], protein folding [ 4 ], interactions between molecules [ 5 ], protein binding [ 6 ], protein adsorption and interactions with both organic and non-organic surfaces [ 7 ], detailed studies of enzymatic activity [ 8 ], drug delivery [ 9 ] and the oligomerisation process [ 10 ], among others.…”