GPU‐accelerated molecular mechanics computations

Anthopoulos, Athanasios; Grimstead, Ian J.; Brancale, Andrea

doi:10.1002/jcc.23384

Cited by 17 publications

(16 citation statements)

References 30 publications

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“…Other approaches to docking include the work by Daunay et al 50 , Zonta et al 51 and Anthopoulos et al 52 . Daunay et al 50 developed a system that modelled flexibility by using a molecular dynamics engine to compute the relevant forces.…”

Section: Interactive Dockingmentioning

confidence: 99%

Haptic-Assisted Interactive Molecular Docking Incorporating Receptor Flexibility

Matthews

Kitao

Laycock

et al. 2019

J. Chem. Inf. Model.

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Haptic-assisted interactive docking tools immerse the user in an environment where intuition and knowledge can be used to help guide the docking process. Here we present such a tool where the user "holds" a rigid ligand via a haptic device through which they feel interaction forces with a flexible receptor biomolecule. To ensure forces transmitted through the haptic device are smooth and stable, they must be updated at a rate greater than 500 Hz. Due to this time constraint, the majority of haptic docking tools do not attempt to model the conformational changes that would occur when molecules interact during binding. Our haptic-assisted docking tool, "Haptimol FlexiDock", models a receptor's conformational response to forces of interaction with a ligand whilst maintaining the required haptic refresh rate. In order to model receptor flexibility we use the method of linear response for which we determine the variance-covariance matrix of atomic fluctuations from the trajectory of an explicit-solvent Molecular Dynamics simulation of the ligand-free receptor molecule. Key to satisfying the time constraint is an eigenvector decomposition of the variance-covariance matrix which enables a good approximation to the conformational response of the receptor to be calculated rapidly. This exploits a feature of protein dynamics whereby most fluctuation occurs within a relatively small subspace. The method is demonstrated on Glutamine Binding Protein in interaction with glutamine, and Maltose Binding Protein in interaction with maltose. For both proteins the movement that occurs when the ligand is docked near to its binding site matches the experimentally determined movement well. It is thought that this tool will be particularly useful for structure-based drug design.

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Section: Interactive Dockingmentioning

confidence: 99%

Haptic-Assisted Interactive Molecular Docking Incorporating Receptor Flexibility

Matthews

Kitao

Laycock

et al. 2019

J. Chem. Inf. Model.

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“…Anthopoulos et.al. applied a GPU-based force calculation approach [30] to their haptic-driven molecular modelling simulator [31] in order to evaluate the induced fit effect during protein-drug docking. Their approach addresses 70 flexibility to some degree, but not at haptic refresh rates since it updates the forces at 33Hz (30ms response time).…”

Section: Introductionmentioning

confidence: 99%

Adaptive GPU-accelerated force calculation for interactive rigid molecular docking using haptics

Iakovou

Hayward

Laycock

2015

Journal of Molecular Graphics and Modelling

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Molecular docking systems model and simulate in silico the interactions of intermolecular binding. Haptics-assisted docking enables the user to interact with the simulation via their sense of touch but a stringent time constraint on the computation of forces is imposed due to the sensitivity of the human haptic system.To simulate high fidelity smooth and stable feedback the haptic feedback loop should run at rates of 500Hz to 1kHz. We present an adaptive force calculation approach that can be executed in parallel on a wide range of Graphics Processing Units (GPUs) for interactive haptics-assisted docking with wider applicability to molecular simulations. Prior to the interactive session either the regular grid or an octree is selected according to the available GPU memory to determine the set of interatomic interactions within a cutoff distance. The total force is then calculated from this set. The approach can achieve force updates in less than 2ms for molecular structures comprising hundreds of thousands of atoms each, with performance improvements of up to 90 times the speed of current CPU-based force calculation approaches used in interactive docking. Furthermore, it overcomes * Corresponding author Email addresses: sjh@cmp.uea.ac.uk (Steven Hayward), s.laycock@uea.ac.uk (Stephen D. Laycock) Graphics and Modelling June 8, 2015 several computational limitations of previous approaches such as pre-computed force grids, and could potentially be used to model receptor flexibility at haptic refresh rates. Preprint submitted to Journal of Molecular

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“…However, the generation and use of such a list requires random memory access to large arrays of atomic coordinates, which is unfavorable on the GPU architecture. This problem has been discussed and different solutions suggested, none of which completely solves the issue …”

Section: Introductionmentioning

confidence: 99%

“…This problem has been discussed and different solutions suggested, none of which completely solves the issue. [3,16,23,27] Reported performance increases due to the transition from computing on a CPU to a GPU depend significantly on the quality of both the CPU and the GPU codes that are being compared as well as on the hardware where the codes are run. Recent statistics from NVIDIA suggests that in an optimal scenario, one GPU provides around 103 speed improvement for DP calculations compared to an eight-core CPU.…”

Section: Introductionmentioning

confidence: 99%

Algorithms forGPU‐based molecular dynamics simulations of complex fluids: Applications to water, mixtures, and liquid crystals

et al. 2015

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A custom code for molecular dynamics simulations has been designed to run on CUDA-enabled NVIDIA graphics processing units (GPUs). The double-precision code simulates multicomponent fluids, with intramolecular and intermolecular forces, coarse-grained and atomistic models, holonomic constraints, Nosé-Hoover thermostats, and the generation of distribution functions. Algorithms to compute Lennard-Jones and Gay-Berne interactions, and the electrostatic force using Ewald summations, are discussed. A neighbor list is introduced to improve scaling with respect to system size. Three test systems are examined: SPC/E water; an n-hexane/2-propanol mixture; and a liquid crystal mesogen, 2-(4-butyloxyphenyl)-5-octyloxypyrimidine. Code performance is analyzed for each system. With one GPU, a 33-119 fold increase in performance is achieved compared with the serial code while the use of two GPUs leads to a 69-287 fold improvement and three GPUs yield a 101-377 fold speedup.

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GPU‐accelerated molecular mechanics computations

Cited by 17 publications

References 30 publications

Haptic-Assisted Interactive Molecular Docking Incorporating Receptor Flexibility

Haptic-Assisted Interactive Molecular Docking Incorporating Receptor Flexibility

Adaptive GPU-accelerated force calculation for interactive rigid molecular docking using haptics

Algorithms forGPU‐based molecular dynamics simulations of complex fluids: Applications to water, mixtures, and liquid crystals

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