OpenMM 7: Rapid development of high performance algorithms for molecular dynamics

Eastman, Peter; Swails, Jason M.; Chodera, John D.; McGibbon, Robert T.; Zhao, Yulan; Beauchamp, Kyle A.; Wang, Lee‐Ping; Simmonett, Andrew C.; Harrigan, Matthew P.; Stern, Chaya; Wiewiora, Rafal; Brooks, Bernard R.; Pande, Vijay S.

doi:10.1371/journal.pcbi.1005659

Cited by 2,143 publications

(1,884 citation statements)

References 35 publications

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“…Following (Doyle et al, 2014), where we investigated the effect of a fixed chromatin loop 29 , we modeled chromatin as a semi-flexible polymer fiber with excluded volume interactions, ( Methods , Supplemental Note). We performed simulations using OpenMM 30,31 , and calculated simulated contact maps (Fig 3a), spatial distance distributions (Fig 3b,c), and average spatial distance maps (Supplemental Fig2b) from the simulated ensemble of conformations.…”

Section: Resultsmentioning

confidence: 99%

FISH-ing for captured contacts: towards reconciling FISH and 3C

2017

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Chromosome conformation capture (3C) and fluorescence in-situ hybridization (FISH) are two widely-used technologies that provide distinct readouts of 3D chromosome organization. While both technologies can assay locus-specific organization, how to integrate views from 3C, or genome-wide Hi-C, and FISH is far from solved. Contact frequency, measured by Hi-C, and spatial distance, measured by FISH, are often assumed to quantify the same phenomena and used interchangeably. Here, however, we demonstrate that contact frequency is distinct from average spatial distance, both in polymer simulations and in experimental data. Performing a systematic analysis of the technologies, we show this distinction can create a seemingly-paradoxical relationship between 3C and FISH, both in minimal polymer models with dynamic looping interactions and in loop extrusion simulations. Together, our results indicate that cross-validation of Hi-C and FISH should be carefully designed, and that jointly considering contact frequency and spatial distance is crucial for fully understanding chromosome organization.

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Section: Resultsmentioning

confidence: 99%

FISH-ing for captured contacts: towards reconciling FISH and 3C

2017

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“…Perhaps the most affordable and impactful of these are platforms using graphics processing units (GPUs). 1–7 …”

Section: Introductionmentioning

confidence: 99%

GPU-Accelerated Molecular Dynamics and Free Energy Methods in Amber18: Performance Enhancements and New Features

Cerutti

Mermelstein

et al. 2018

J. Chem. Inf. Model.

375

311

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We report progress in GPU-accelerated molecular dynamics and free energy methods in Amber18. Of particular interest is the development of alchemical free energy algorithms, including free energy perturbation and thermodynamic integration methods with support for non-linear softcore potential and parameter interpolation transformation pathways. These methods can be used in conjunction with enhanced sampling techniques such as replica exchange, constant pH molecular dynamics and new 12-6-4 potentials for metal ions. Additional performance enhancements have been made that enable appreciable speed-up on GPUs relative to the previous software release.

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“…28,32 The GROMOS and GROMACS programs can utilize GPUs for those parts of a system not undergoing an alchemical transformation, 27 and the OpenMM program can utilize GPUs to perform BAR and MBAR free energy calculations. 33–36 Other programs, like CHARMM, contain interfaces to OpenMM. 28 The incompatibility between CHARMM’s free energy module and the other internal software features motivated Boresch and Bruckner to explore alchemical pathways that can be performed as a series of regular MD simulations.…”

Section: Introductionmentioning

confidence: 99%

“…The parameter-interpolated free energy perturbation (PI-FEP) method was pioneered by Jorgensen 38 and continues to be used in the BOSS program. 39 The parameter-interpolated BAR and MBAR methods (PI-BAR and PI-MBAR) have previously been described 36 using the OpenMM program, 40 and this framework has recently been extended to the Tinker-OpenMM module 41 for applications using the AMOEBA force field. 34,42–44 Application of the PI-BAR method has been shown to be a practical alternative to using soft-core potentials.…”

Section: Introductionmentioning

confidence: 99%

A GPU-Accelerated Parameter Interpolation Thermodynamic Integration Free Energy Method

Giese

York

2018

J. Chem. Theory Comput.

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There has been a resurgence of interest in free energy methods motivated by the performance enhancements offered by molecular dynamics (MD) software written for specialized hardware, such as graphics processing units (GPUs). In this work, we exploit the properties of a parameter-interpolated thermodynamic integration (PI-TI) method to connect states by their molecular mechanical (MM) parameter values. This pathway is shown to be better behaved for Mg2+ → Ca2+ transformations than traditional linear alchemical pathways (with and without soft-core potentials). The PI-TI method has the practical advantage that no modification of the MD code is required to propagate the dynamics, and unlike with linear alchemical mixing, only one electrostatic evaluation is needed (e.g., single call to particle-mesh Ewald) leading to better performance. In the case of AMBER, this enables all the performance benefits of GPU-acceleration to be realized, in addition to unlocking the full spectrum of features available within the MD software, such as Hamiltonian replica exchange (HREM). The TI derivative evaluation can be accomplished efficiently in a post-processing step by reanalyzing the statistically independent trajectory frames in parallel for high throughput. We also show how one can evaluate the particle mesh Ewald contribution to the TI derivative evaluation without needing to perform two reciprocal space calculations. We apply the PI-TI method with HREM on GPUs in AMBER to predict pKa values in double stranded RNA molecules and make comparison with experiments. Convergence to under 0.25 units for these systems required 100 ns or more of sampling per window and coupling of windows with HREM. We find that MM charges derived from ab initio QM/MM fragment calculations improve the agreement between calculation and experimental results.

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OpenMM 7: Rapid development of high performance algorithms for molecular dynamics

Cited by 2,143 publications

References 35 publications

FISH-ing for captured contacts: towards reconciling FISH and 3C

FISH-ing for captured contacts: towards reconciling FISH and 3C

GPU-Accelerated Molecular Dynamics and Free Energy Methods in Amber18: Performance Enhancements and New Features

A GPU-Accelerated Parameter Interpolation Thermodynamic Integration Free Energy Method

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