Efficiency of linked cell algorithms

The linked cell list algorithm is an essential part of molecular simulation software, both molecular dynamics and Monte Carlo. Though it scales linearly with the number of particles, there has been a constant interest in increasing its efficiency, because a large part of CPU time is spent to identify the interacting particles. Several recent publications proposed improvements to the algorithm and investigated their efficiency by applying them to particular setups. In this publication we develop a general method to evaluate the efficiency of these algorithms, which is mostly independent of the parameters of the simulation, and test it for a number of linked cell list algorithms. We also propose a combination of linked cell reordering and interaction sorting that shows a good efficiency for a broad range of simulation setups.Comment: Submitted to Computer Physics Communications on 22 December 2009, still awaiting a referee repor

Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born

We present an implementation of generalized Born implicit solvent all-atom classical molecular dynamics (MD) within the AMBER program package that runs entirely on CUDA enabled NVIDIA graphics processing units (GPUs). We discuss the algorithms that are used to exploit the processing power of the GPUs and show the performance that can be achieved in comparison to simulations on conventional CPU clusters. The implementation supports three different precision models in which the contributions to the forces are calculated in single precision floating point arithmetic but accumulated in double precision (SPDP), or everything is computed in single precision (SPSP) or double precision (DPDP). In addition to performance, we have focused on understanding the implications of the different precision models on the outcome of implicit solvent MD simulations. We show results for a range of tests including the accuracy of single point force evaluations and energy conservation as well as structural properties pertainining to protein dynamics. The numerical noise due to rounding errors within the SPSP precision model is sufficiently large to lead to an accumulation of errors which can result in unphysical trajectories for long time scale simulations. We recommend the use of the mixed-precision SPDP model since the numerical results obtained are comparable with those of the full double precision DPDP model and the reference double precision CPU implementation but at significantly reduced computational cost. Our implementation provides performance for GB simulations on a single desktop that is on par with, and in some cases exceeds, that of traditional supercomputers

Evaluating force field accuracy with long-time simulations of a tryptophan zipper peptide

We have combined a custom implementation of the fast multiple-time-stepping LN integrator with parallel tempering to explore folding properties of small peptides in implicit solvent on the time scale of microseconds. We applied this algorithm to the synthetic {\beta}-hairpin trpzip2 and one of its sequence variants W2W9. Each simulation consisted of over 12 {\mu}s of aggregated virtual time. Several measures of folding behavior showed convergence, allowing comparison with experimental equilibrium properties. Our simulations suggest that the electrostatic interaction of tryptophan sidechains is responsible for much of the stability of the native fold. We conclude that the ff99 force field combined with ff96 {\phi} and {\psi} dihedral energies and implicit solvent can reproduce plausible folding behavior in both trpzip2 and W2W9.Comment: 10 pages, 11 figures, submitted to the Journal of Chemical Physics on June 28, 201

CHARMM: The biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983. © 2009 Wiley Periodicals, Inc.J Comput Chem, 2009.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63074/1/21287_ftp.pd

Using Novel Approaches for Navigating Complex Energy Landscapes: Ion Channel Conductance using Hyperdynamics and Human-Guided Global Optimization of Lennard-Jones Clusters

Molecular dynamics (MD) is a widely used tool to study molecular systems on atomic level. However, the timescale of a traditional MD simulation is typically limited to nanoseconds. Thus many interesting processes that occur on microseconds or larger timescale can\u27t be studied. Hyperdynamics provides a way to extend the timescale of MD simulation. In hyperdynamics, MD is performed on a biased potential then corrected to get true dynamics provided certain conditions are met. Here, we tried to study potassium channel conductance using the hyperdynamics method with a bias potential constructed based on the potential of mean force of ion translocation through the selective filter of a potassium ion channel. However, when MD was performed on this biased potential, no ion translocation events were observed. Although some new insights were gained into the rate-limiting steps for ion mobility in this system from these negative results, no further studies are planned with this project. The second project is based on the assumption that hybrid human{computational algorithm is more efficient than purely computational algorithm itself. Such ideas have already been studied by many \crowd-sourcing games, such as Foldit [1] for the protein structure prediction problem, and QuantumMoves [2] for quantum physics. Here, the same idea is applied to cluster structure optimization. A virtual reality android cellphone app was developed to study global optimization of Lennard-Jones clusters with both computational algorithm and hybrid human{computational algorithm. Using linear mixed model analysis, we found statistically significant differences between the expected runtime of both methods, at least for cluster of certain sizes. Further analysis of the data showing human intelligence weakened the strong dependence of the efficiency of the computational method on cluster sizes. We hypothesis that this is due to that humans are able to make large moves that allows the algorithm to cover a large region in the potential energy surface faster. Further studies with more cluster sizes are needed to draw a more complete conclusion. Human intelligence can potentially be integrated into more advanced optimization technique and applied to more complicated optimization problems in the future. Patterns analysis of human behaviors during the optimization process can be conducted to gain insights of mechanisms and strategies of optimization process

A local resampling trick for focused molecular dynamics

We describe a method that focuses sampling effort on a user-defined selection of a large system, which can lead to substantial decreases in computational effort by speeding up the calculation of nonbonded interactions. A naive approach can lead to incorrect sampling if the selection depends on the configuration in a way that is not accounted for. We avoid this pitfall by introducing appropriate auxiliary variables. This results in an implementation that is closely related to configurational freezing and elastic barrier dynamical freezing. We implement the method and validate that it can be used to supplement conventional molecular dynamics in free energy calculations (absolute hydration and relative binding)

Development of Improved Torsional Potentials in Classical Force Field Models of Poly (Lactic Acid)

In this work, existing force field descriptions of poly (lactic acid), or PLA, were improved by modifying the torsional potential energy terms to more accurately model the bond rotational behavior of PLA. Extensive calculations were carried out using density functional theory (DFT), for small PLA molecules in vacuo, and also using DFT with a continuum model to approximate the electronic structure of PLA in its condensed phase. From these results, improved force field parameters were developed using a combination of the OPLS and CHARMM force fields. The new force field, PLAFF2, is an update to the previously developed PLAFF model developed in David Bruce\u27s group, and results in more realistic conformational distributions during simulation of bulk amorphous PLA. It is demonstrated that the PLAFF2 model retains the accuracy of the original PLAFF in simulating the crystalline α polymorph of PLA. The PLAFF2 model has superior performance to any other publicly available force field for use with PLA; hence, we recommend its use in future modeling studies on the material, whether in its crystalline or amorphous form

An efficient algorithm for conformational search of macrocyclic molecules

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 45-47).by Cheuk-san (Edward) Wang.M.S