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  • Simulation Parameters used in the Study titled "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method"

    work
    Creator:
    Larson, Ronald G., Wen, Fei, Huang, Wenjun, and Huang, Ming
    Description:
    We provide the parameters used in Umbrella Sampling simulations reported in our study "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method", namely the set positions and spring constants for each window in simulations. Two tables are provided. Table 1 lists the names of the peptides and their corresponding sequences. Table 2 lists the parameters. The abstract of our work is the following: We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with Weighted Histogram Analysis Method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse-grained (CG) force field (MARTINI) is less prone to significant error induced by biased-sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3-4 residue peptide segments while leaving the remain-ing peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and relia-bly estimate the binding free energy between an arbitrary peptide and an MHC class II molecule.
    Keyword:
    Molecular Dynamics, Binding Free Energy, Protein, MHC, and Coarse-Grained
    Citation to related publication:
    M. Huang, W. Huang, F. Wen, R. G. Larson. J. Comput. Chem. 2017, 38, 2007–2019.  https://doi.org/10.1002/jcc.24845
    Discipline:
    Science and Engineering