The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Shankar Subramaniam - One of the best experts on this subject based on the ideXlab platform.
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On Brownian Dynamics Simulation of Nanoparticle Aggregation
Industrial & Engineering Chemistry Research, 2008Co-Authors: Sergiy Markutsya, Shankar Subramaniam, R. Dennis Vigil, Rodney O. FoxAbstract:Accurate simulation and control of nanoparticle aggregation in chemical reactors requires that population balance equations be solved by using realistic expressions for aggregation and breakage rate kernels. Obtaining such expressions requires that atomistic simulation approaches that can account for microscopic details of particle collisions be used. In principle, molecular Dynamics simulations can provide the needed microscopic information, but because of the separation in length scales between the aggregates and solvent molecules, such simulations are too costly. Brownian Dynamics simulations provide an alternative to the molecular Dynamics approach for simulation of particle aggregation, but there has been no systematic attempt to validate the Brownian Dynamics method for this class of problems. In this work we attempt to develop a better understanding of Brownian Dynamics simulations of aggregation by (1) developing convergence criteria, (2) determining criteria for aggregation to occur in BD simulations using dimensionless variables, and (3) directly comparing BD and MD simulation predictions for a model aggregation problem.
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bimolecular reaction simulation using weighted ensemble Brownian Dynamics and the university of houston Brownian Dynamics program
Biophysical Journal, 2000Co-Authors: Atipat Rojnuckarin, Dennis R Livesay, Shankar SubramaniamAbstract:We discuss here the implementation of the Weighted Ensemble Brownian (WEB) Dynamics algorithm of Huber and Kim in the University of Houston Brownian Dynamics (UHBD) suite of programs and its application to bimolecular association problems. WEB Dynamics is a biased Brownian Dynamics (BD) algorithm that is more efficient than the standard Northrup-Allison-McCammon (NAM) method in cases where reaction events are infrequent because of intervening free energy barriers. Test cases reported here include the Smoluchowski rate for association of spheres, the association of the enzyme copper-zinc superoxide dismutase with superoxide anion, and the binding of the superpotent sweetener N-(p-cyanophenyl)-N'-(diphenylmethyl)-guanidinium acetic acid to a monoclonal antibody fragment, NC6.8. Our results show that the WEB Dynamics algorithm is a superior simulation method for enzyme-substrate reaction encounters with large free energy barriers.
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Biased Brownian Dynamics for rate constant calculation.
Biophysical journal, 2000Co-Authors: Gang Zou, Robert D. Skeel, Shankar SubramaniamAbstract:An enhanced sampling method-biased Brownian Dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian Dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampling of trajectories is then biased, but the sampling is unbiased when the trajectory outcomes are multiplied by their weights. With a suitable choice of the biasing force, more reacted trajectories are sampled. As a consequence, the variance of the estimate is reduced. In our test case, biased Brownian Dynamics gives a sevenfold improvement in central processing unit (CPU) time with the choice of a simple centripetal biasing force.
Gang Zou - One of the best experts on this subject based on the ideXlab platform.
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Robust biased Brownian Dynamics for rate constant calculation
Biophysical journal, 2003Co-Authors: Robert D. Skeel, Gang ZouAbstract:A reaction probability is required to calculate the rate constant of a diffusion-dominated reaction. Due to the complicated geometry and potentially high dimension of the reaction probability problem, it is usually solved by a Brownian Dynamics simulation, also known as a random walk or path integral method, instead of solving the equivalent partial differential equation by a discretization method. Building on earlier work, this article completes the development of a robust importance sampling algorithm for Brownian Dynamics—i.e., biased Brownian Dynamics with weight control—to overcome the high energy and entropy barriers in biomolecular association reactions. The biased Brownian Dynamics steers sampling by a bias force, and the weight control algorithm controls sampling by a target weight. This algorithm is optimal if the bias force and the target weight are constructed from the solution of the reaction probability problem. In reality, an approximate reaction probability has to be used to construct the bias force and the target weight. Thus, the performance of the algorithm depends on the quality of the approximation. Given here is a method to calculate a good approximation, which is based on the selection of a reaction coordinate and the variational formulation of the reaction probability problem. The numerically approximated reaction probability is shown by computer experiments to give a factor-of-two speedup over the use of a purely heuristic approximation. Also, the fully developed method is compared to unbiased Brownian Dynamics. The tests for human superoxide dismutase, Escherichia coli superoxide dismutase, and antisweetener antibody NC6.8, show speedups of 17, 35, and 39, respectively. The test for reactions between two model proteins with orientations shows speedups of 2578 for one set of configurations and 3341 for another set of configurations.
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Biased Brownian Dynamics for rate constant calculation.
Biophysical journal, 2000Co-Authors: Gang Zou, Robert D. Skeel, Shankar SubramaniamAbstract:An enhanced sampling method-biased Brownian Dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian Dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampling of trajectories is then biased, but the sampling is unbiased when the trajectory outcomes are multiplied by their weights. With a suitable choice of the biasing force, more reacted trajectories are sampled. As a consequence, the variance of the estimate is reduced. In our test case, biased Brownian Dynamics gives a sevenfold improvement in central processing unit (CPU) time with the choice of a simple centripetal biasing force.
S. Kim - One of the best experts on this subject based on the ideXlab platform.
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Weighted-ensemble Brownian Dynamics simulations for protein association reactions
Biophysical journal, 1996Co-Authors: G.a. Huber, S. KimAbstract:A new method, weighted-ensemble Brownian Dynamics, is proposed for the simulation of protein-association reactions and other events whose frequencies of outcomes are constricted by free energy barriers. The method features a weighted ensemble of trajectories in configuration space with energy levels dictating the proper correspondence between "particles" and probability. Instead of waiting a very long time for an unlikely event to occur, the probability packets are split, and small packets of probability are allowed to diffuse almost immediately into regions of configuration space that are less likely to be sampled. The method has been applied to the Northrup and Erickson (1992) model of docking-type diffusion-limited reactions and yields reaction rate constants in agreement with those obtained by direct Brownian simulation, but at a fraction of the CPU time (10(-4) to 10(-3), depending on the model). Because the method is essentially a variant of standard Brownian Dynamics algorithms, it is anticipated that weighted-ensemble Brownian Dynamics, in conjunction with biophysical force models, can be applied to a large class of association reactions of interest to the biophysics community.
Robert D. Skeel - One of the best experts on this subject based on the ideXlab platform.
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Robust biased Brownian Dynamics for rate constant calculation
Biophysical journal, 2003Co-Authors: Robert D. Skeel, Gang ZouAbstract:A reaction probability is required to calculate the rate constant of a diffusion-dominated reaction. Due to the complicated geometry and potentially high dimension of the reaction probability problem, it is usually solved by a Brownian Dynamics simulation, also known as a random walk or path integral method, instead of solving the equivalent partial differential equation by a discretization method. Building on earlier work, this article completes the development of a robust importance sampling algorithm for Brownian Dynamics—i.e., biased Brownian Dynamics with weight control—to overcome the high energy and entropy barriers in biomolecular association reactions. The biased Brownian Dynamics steers sampling by a bias force, and the weight control algorithm controls sampling by a target weight. This algorithm is optimal if the bias force and the target weight are constructed from the solution of the reaction probability problem. In reality, an approximate reaction probability has to be used to construct the bias force and the target weight. Thus, the performance of the algorithm depends on the quality of the approximation. Given here is a method to calculate a good approximation, which is based on the selection of a reaction coordinate and the variational formulation of the reaction probability problem. The numerically approximated reaction probability is shown by computer experiments to give a factor-of-two speedup over the use of a purely heuristic approximation. Also, the fully developed method is compared to unbiased Brownian Dynamics. The tests for human superoxide dismutase, Escherichia coli superoxide dismutase, and antisweetener antibody NC6.8, show speedups of 17, 35, and 39, respectively. The test for reactions between two model proteins with orientations shows speedups of 2578 for one set of configurations and 3341 for another set of configurations.
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Biased Brownian Dynamics for rate constant calculation.
Biophysical journal, 2000Co-Authors: Gang Zou, Robert D. Skeel, Shankar SubramaniamAbstract:An enhanced sampling method-biased Brownian Dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian Dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampling of trajectories is then biased, but the sampling is unbiased when the trajectory outcomes are multiplied by their weights. With a suitable choice of the biasing force, more reacted trajectories are sampled. As a consequence, the variance of the estimate is reduced. In our test case, biased Brownian Dynamics gives a sevenfold improvement in central processing unit (CPU) time with the choice of a simple centripetal biasing force.
Dennis R Livesay - One of the best experts on this subject based on the ideXlab platform.
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bimolecular reaction simulation using weighted ensemble Brownian Dynamics and the university of houston Brownian Dynamics program
Biophysical Journal, 2000Co-Authors: Atipat Rojnuckarin, Dennis R Livesay, Shankar SubramaniamAbstract:We discuss here the implementation of the Weighted Ensemble Brownian (WEB) Dynamics algorithm of Huber and Kim in the University of Houston Brownian Dynamics (UHBD) suite of programs and its application to bimolecular association problems. WEB Dynamics is a biased Brownian Dynamics (BD) algorithm that is more efficient than the standard Northrup-Allison-McCammon (NAM) method in cases where reaction events are infrequent because of intervening free energy barriers. Test cases reported here include the Smoluchowski rate for association of spheres, the association of the enzyme copper-zinc superoxide dismutase with superoxide anion, and the binding of the superpotent sweetener N-(p-cyanophenyl)-N'-(diphenylmethyl)-guanidinium acetic acid to a monoclonal antibody fragment, NC6.8. Our results show that the WEB Dynamics algorithm is a superior simulation method for enzyme-substrate reaction encounters with large free energy barriers.
