scholarly journals Peptide Gaussian accelerated molecular dynamics (Pep-GaMD): Enhanced sampling and free energy and kinetics calculations of peptide binding

2020 ◽  
Vol 153 (15) ◽  
pp. 154109 ◽  
Author(s):  
Jinan Wang ◽  
Yinglong Miao
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Peptide Binding ◽  
Enhanced Sampling ◽  
Accelerated Molecular Dynamics

scholarly journals Peptide Gaussian accelerated molecular dynamics (Pep-GaMD): Enhanced sampling and free energy and kinetics calculations of peptide binding

2020 ◽  
Author(s):  
Jinan Wang ◽  
Yinglong Miao
Keyword(s):  
Molecular Dynamics ◽  
Potential Energy ◽  
Protein Interactions ◽  
Peptide Binding ◽  
Computational Method ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Accelerated Molecular Dynamics ◽  
High Flexibility ◽  
Binding Free Energies

AbstractPeptides 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.Significance StatementWe have developed a new computational method “Pep-GaMD” for enhanced sampling of peptide-protein interactions based on the Gaussian accelerated molecular dynamics (GaMD) technique. Pep-GaMD works by selectively boosting the essential potential energy of the peptide to effectively model its high flexibility. In addition, another boost potential can be 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. Dual-boost Pep-GaMD has captured repetitive peptide dissociation and binding events within significantly shorter simulation time (microsecond) than conventional molecular dynamics. Compared with previous enhanced sampling methods, Pep-GaMD is easier to use and more efficient for unconstrained enhanced sampling of peptide binding and unbinding, which provides a novel physics-based approach to calculating peptide binding free energies and kinetics.

SPONGE : A GPU‐Accelerated Molecular Dynamics Package with Enhanced Sampling and AI‐Driven Algorithms

2021 ◽  
Author(s):  
Yu‐Peng Huang ◽  
Yijie Xia ◽  
Lijiang Yang ◽  
Jiachen Wei ◽  
Yi Isaac Yang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Enhanced Sampling ◽  
Accelerated Molecular Dynamics

scholarly journals An Efficient GaMD Multi-Level Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems

2021 ◽  
Author(s):  
Fréderic Célerse ◽  
Theo Jaffrelot-Inizan ◽  
Louis Lagardère ◽  
Olivier Adjoua ◽  
Pierre Monmarché ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Adaptive Sampling ◽  
Sampling Strategy ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Enhanced Sampling ◽  
Polarizable Force Field ◽  
Accelerated Molecular Dynamics ◽  
Polarizable Force Fields ◽  
Multi Level

We detail a novel multi-level enhanced sampling strategy grounded on Gaussian accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs-accelerated implementation within the Tinker-HP molecular dynamics package. We then introduce the new "dual-water" mode and its use with the flexible AMOEBA polarizable force field. By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups thanks to the use of fast multiple--timestep integrators. To further reduce time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD—US/dual-water approach is tested on the 1D Potential of Mean Force (PMF) of the CD2-CD58 system (168000 atoms) allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added enabling AS-GaMD capabilities but also the introduction of the new Adaptive Sampling--US--GaMD (ASUS--GaMD) scheme. The highly parallel ASUS--GaMD setup decreases time to convergence by respectively 10 and 20 compared to GaMD--US and US.

Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information

2015 ◽  
Vol 11 (7) ◽  
pp. 3446-3454 ◽  
Author(s):  
Isidro Cortes-Ciriano ◽  
Guillaume Bouvier ◽  
Michael Nilges ◽  
Luca Maragliano ◽  
Thérèse E. Malliavin
Keyword(s):  
Molecular Dynamics ◽  
Enhanced Sampling ◽  
Low Resolution ◽  
Accelerated Molecular Dynamics
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