Peptides mediate up to 40% of known protein–protein interactions in higher eukaryotes and play an important role in cellular signaling. However, it is challenging to simulate both binding and unbinding of peptides and calculate peptide binding free energies through conventional molecular dynamics, due to long biological timescales and extremely high flexibility of the peptides. Based on the Gaussian accelerated molecular dynamics (GaMD) enhanced sampling technique, we have developed a new computational method “Pep-GaMD,” which selectively boosts essential potential energy of the peptide in order to effectively model its high flexibility. In addition, another boost potential is applied to the remaining potential energy of the entire system in a dual-boost algorithm. Pep-GaMD has been demonstrated on binding of three model peptides to the SH3 domains. Independent 1 µs dual-boost Pep-GaMD simulations have captured repetitive peptide dissociation and binding events, which enable us to calculate peptide binding thermodynamics and kinetics. The calculated binding free energies and kinetic rate constants agreed very well with available experimental data. Furthermore, the all-atom Pep-GaMD simulations have provided important insights into the mechanism of peptide binding to proteins that involves long-range electrostatic interactions and mainly conformational selection. In summary, Pep-GaMD provides a highly efficient, easy-to-use approach for unconstrained enhanced sampling and calculations of peptide binding free energies and kinetics.
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21 October 2020
Research Article|
October 19 2020
Peptide Gaussian accelerated molecular dynamics (Pep-GaMD): Enhanced sampling and free energy and kinetics calculations of peptide binding
Jinan Wang
;
Jinan Wang
Center for Computational Biology and Department of Molecular Biosciences, University of Kansas
, Lawrence, Kansas 66047, USA
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Yinglong Miao
Yinglong Miao
a)
Center for Computational Biology and Department of Molecular Biosciences, University of Kansas
, Lawrence, Kansas 66047, USA
a)Author to whom correspondence should be addressed: miao@ku.edu
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a)Author to whom correspondence should be addressed: miao@ku.edu
Note: This paper is part of the JCP Special Topic on Classical Molecular Dynamics (MD) Simulations: Codes, Algorithms, Force Fields, and Applications.
J. Chem. Phys. 153, 154109 (2020)
Article history
Received:
July 13 2020
Accepted:
September 22 2020
Citation
Jinan Wang, Yinglong Miao; Peptide Gaussian accelerated molecular dynamics (Pep-GaMD): Enhanced sampling and free energy and kinetics calculations of peptide binding. J. Chem. Phys. 21 October 2020; 153 (15): 154109. https://doi.org/10.1063/5.0021399
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