Journal Of Computational Chemistry [J Comput Chem] 2010 Apr 30; Vol. 31 (6), pp. 1268-72.
Algorithms, Lipid Bilayers chemistry, Molecular Dynamics Simulation, and Proteins chemistry
We describe an algorithm for computing nonbonded interactions with cutoffs on a graphics processing unit. We have incorporated it into OpenMM, a library for performing molecular simulations on high-performance computer architectures. We benchmark it on a variety of systems including boxes of water molecules, proteins in explicit solvent, a lipid bilayer, and proteins with implicit solvent. The results demonstrate that its performance scales linearly with the number of atoms over a wide range of system sizes, while being significantly faster than other published algorithms. (2009 Wiley Periodicals, Inc.)
We describe a complete implementation of all-atom protein molecular dynamics running entirely on a graphics processing unit (GPU), including all standard force field terms, integration, constraints, and implicit solvent. We discuss the design of our algorithms and important optimizations needed to fully take advantage of a GPU. We evaluate its performance, and show that it can be more than 700 times faster than a conventional implementation running on a single CPU core. ((c) 2009 Wiley Periodicals, Inc.)
Journal Of Computational Chemistry [J Comput Chem] 2008 Apr 15; Vol. 29 (5), pp. 694-700.
Algorithms, Kinetics, Reproducibility of Results, Static Electricity, Computer Simulation, Models, Chemical, Protein Folding, and Proteins chemistry
Molecular dynamics simulations are a useful tool for characterizing protein folding pathways. There are several methods of treating electrostatic forces in these simulations with varying degrees of physical fidelity and computational efficiency. In this article, we compare the reaction field (RF) algorithm, particle-mesh Ewald (PME), and tapered cutoffs with increasing cutoff radii to address the impact of the electrostatics method employed on the folding kinetics. We quantitatively compare different methods by a correlation of quantitative measures of protein folding kinetics. The results of these comparisons show that for protein folding kinetics, the RF algorithm can quantitatively reproduce the kinetics of the more costly PME algorithm. These results not only assist the selection of appropriate algorithms for future simulations, but also give insight on the role that long-range electrostatic forces have in protein folding. ((c) 2007 Wiley Periodicals, Inc.)
Journal Of Computational Chemistry [J Comput Chem] 2005 May; Vol. 26 (7), pp. 682-90.
Algorithms, Computer Simulation, Thermodynamics, Torsion Abnormality, Models, Molecular, Peptides chemistry, Protein Conformation, and Proteins chemistry
The kinetic and thermodynamic aspects of the helix-coil transition in polyalanine-based peptides have been studied at the ensemble level using a distributed computing network. This study builds on a previous report, which critically assessed the performance of several contemporary force fields in reproducing experimental measurements and elucidated the complex nature of helix-coil systems. Here we consider the effects of modifying backbone torsions and the scaling of noncovalent interactions. Although these elements determine the potential of mean force between atoms separated by three covalent bonds (and thus largely determine the local conformational distributions observed in simulation), we demonstrate that the interplay between these factors is both complex and force field dependent. We quantitatively assess the heliophilicity of several helix-stabilizing potentials as well as the changes in heliophilicity resulting from such modifications, which can "make or break" the accuracy of a given force field, and our findings suggests that future force field development may need to better consider effect that vary with peptide length. This report also serves as an example of the utility of distributed computing in analyzing and improving upon contemporary force fields at the level of absolute ensemble equilibrium, the next step in force field development.
Journal Of Computational Chemistry [J Comput Chem] 2003 Sep; Vol. 24 (12), pp. 1432-6.
Algorithms, Computer Simulation, Solvents, Thermodynamics, Viscosity, Models, Molecular, Protein Folding, Proteins chemistry, and Tryptophan chemistry
By using distributed computing techniques and a supercluster of more than 20,000 processors we simulated folding of a 20-residue Trp Cage miniprotein in atomistic detail with implicit GB/SA solvent at a variety of solvent viscosities (gamma). This allowed us to analyze the dependence of folding rates on viscosity. In particular, we focused on the low-viscosity regime (values below the viscosity of water). In accordance with Kramers' theory, we observe approximately linear dependence of the folding rate on 1/gamma for values from 1-10(-1)x that of water viscosity. However, for the regime between 10(-4)-10(-1)x that of water viscosity we observe power-law dependence of the form k approximately gamma(-1/5). These results suggest that estimating folding rates from molecular simulations run at low viscosity under the assumption of linear dependence of rate on inverse viscosity may lead to erroneous results. (Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 1432-1436, 2003)