ACCELERATED MOLECULAR DYNAMICS: AN EFFICIENT ENHANCED SAMPLING METHOD FOR BIOMOLECULAR SIMULATIONS

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.

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

Journal of Chemical Theory and Computation ◽

10.1021/acs.jctc.5b00153 ◽

2015 ◽

Vol 11 (7) ◽

pp. 3446-3454 ◽

Cited By ~ 10

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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Accelerated Molecular Dynamics Applied to the Peptaibol Folding Problem

International Journal of Molecular Sciences ◽

10.3390/ijms20174268 ◽

2019 ◽

Vol 20 (17) ◽

pp. 4268

Author(s):

Chetna Tyagi ◽

Tamás Marik ◽

Csaba Vágvölgyi ◽

László Kredics ◽

Ferenc Ötvös

Keyword(s):

Molecular Dynamics ◽

Enhanced Sampling ◽

New Approach ◽

E Coli ◽

Accelerated Molecular Dynamics ◽

Simulation Techniques ◽

Unfolded State ◽

Folding Dynamics ◽

Transmembrane Channels ◽

Dynamics Simulations

The use of enhanced sampling molecular dynamics simulations to facilitate the folding of proteins is a relatively new approach which has quickly gained momentum in recent years. Accelerated molecular dynamics (aMD) can elucidate the dynamic path from the unfolded state to the near-native state, “flattened” by introducing a non-negative boost to the potential. Alamethicin F30/3 (Alm F30/3), chosen in this study, belongs to the class of peptaibols that are 7–20 residue long, non-ribosomally synthesized, amphipathic molecules that show interesting membrane perturbing activity. The recent studies undertaken on the Alm molecules and their transmembrane channels have been reviewed. Three consecutive simulations of ~900 ns each were carried out where N-terminal folding could be observed within the first 100 ns, while C-terminal folding could only be achieved almost after 800 ns. It took ~1 μs to attain the near-native conformation with stronger potential boost which may take several μs worth of classical MD to produce the same results. The Alm F30/3 hexamer channel was also simulated in an E. coli mimicking membrane under an external electric field that correlates with previous experiments. It can be concluded that aMD simulation techniques are suited to elucidate peptaibol structures and to understand their folding dynamics.

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A variational approach to nucleation simulation

Faraday Discussions ◽

10.1039/c6fd00127k ◽

2016 ◽

Vol 195 ◽

pp. 557-568 ◽

Cited By ~ 12

Author(s):

Pablo M. Piaggi ◽

Omar Valsson ◽

Michele Parrinello

Keyword(s):

Molecular Dynamics ◽

Computer Simulation ◽

Free Energy ◽

Variational Approach ◽

Sampling Method ◽

Enhanced Sampling ◽

Technical Problems ◽

Lennard Jones ◽

Dynamics Simulations

We study by computer simulation the nucleation of a supersaturated Lennard-Jones vapor into the liquid phase. The large free energy barriers to transition make the time scale of this process impossible to study by ordinary molecular dynamics simulations. Therefore we use a recently developed enhanced sampling method [Valsson and Parrinello, Phys. Rev. Lett.113, 090601 (2014)] based on the variational determination of a bias potential. We differ from previous applications of this method in that the bias is constructed on the basis of the physical model provided by the classical theory of nucleation. We examine the technical problems associated with this approach. Our results are very satisfactory and will pave the way for calculating the nucleation rates in many systems.

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Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation

Journal of Chemical Theory and Computation ◽

10.1021/acs.jctc.5b00436 ◽

2015 ◽

Vol 11 (8) ◽

pp. 3584-3595 ◽

Cited By ~ 204

Author(s):

Yinglong Miao ◽

Victoria A. Feher ◽

J. Andrew McCammon

Keyword(s):

Molecular Dynamics ◽

Free Energy ◽

Free Energy Calculation ◽

Energy Calculation ◽

Enhanced Sampling ◽

Accelerated Molecular Dynamics

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Exploring Protocols to Build Reservoirs to Accelerate Replica Exchange MD Simulations

10.26434/chemrxiv.12328007 ◽

2020 ◽

Author(s):

koushik kasavajhala ◽

kenneth lam ◽

Carlos Simmerling

Keyword(s):

Amino Acids ◽

Sampling Method ◽

Convergence Rates ◽

Md Simulations ◽

Replica Exchange ◽

Conformational Sampling ◽

Enhanced Sampling ◽

Replica Exchange Molecular Dynamics ◽

The Past ◽

Biomolecular Simulations

Replica Exchange Molecular Dynamics (REMD) is a widely used enhanced sampling method for accelerating biomolecular simulations. During the past two decades, several variants of REMD have been developed to further improve the rate of conformational sampling of REMD. One such variant, Reservoir REMD (RREMD), was shown to improve the rate of conformational sampling by around 5-20x. Despite the significant increase in sampling speed, RREMD methods have not been widely used due to the difficulties in building the reservoir and also due to the code not being available on the GPUs.<br><br>In this work, we ported the AMBER RREMD code onto GPUs making it 20x faster than the CPU code. Then, we explored protocols for building Boltzmann-weighted reservoirs as well as non-Boltzmann reservoirs, and tested how each choice affects the accuracy of the resulting RREMD simulations. We show that, using the recommended protocols outlined here, RREMD simulations can accurately reproduce Boltzmann-weighted ensembles obtained by much more expensive conventional REMD simulations, with at least 15x faster convergence rates even for larger proteins (>50 amino acids) compared to conventional REMD.

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