Topic
Monte Carlo molecular modeling
About: Monte Carlo molecular modeling is a research topic. Over the lifetime, 11307 publications have been published within this topic receiving 409122 citations.
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TL;DR: In this paper, a comparison study has been carried out to test the relative efficiency of Metropolis Monte Carlo and molecular dynamics simulations for conformational sampling, and the test case that has been examine...
Abstract: A comparison study has been carried out to test the relative efficiency of Metropolis Monte Carlo and molecular dynamics simulations for conformational sampling. The test case that has been examine...
140 citations
TL;DR: Some existing methods for parallelization of Markov chain Monte Carlo algorithms are discussed, and a new “pre-fetching” algorithm is proposed to parallelize generation of a single chain.
Abstract: In recent years, parallel processing has become widely available to researchers. It can be applied in an obvious way in the context of Monte Carlo simulation, but techniques for “parallelizing” Markov chain Monte Carlo (MCMC) algorithms are not so obvious, apart from the natural approach of generating multiple chains in parallel. Although generation of parallel chains is generally the easiest approach, in cases where burn-in is a serious problem, it is often desirable to use parallelization to speed up generation of a single chain. This article briefly discusses some existing methods for parallelization of MCMC algorithms, and proposes a new “pre-fetching” algorithm to parallelize generation of a single chain.
140 citations
TL;DR: Application to the conformational optimization of a tetrapeptide demonstrates that the algorithm is more effective in locating low energy minima than standard simulated annealing based on molecular dynamics or Monte Carlo methods.
Abstract: A Monte Carlo simulated annealing algorithm based on the generalized entropy of Tsallis is presented. The algorithm obeys detailed balance and reduces to a steepest descent algorithm at low temperatures. Application to the conformational optimization of a tetrapeptide demonstrates that the algorithm is more effective in locating low energy minima than standard simulated annealing based on molecular dynamics or Monte Carlo methods.
139 citations
TL;DR: A systematic approach is presented to quasi-random numbers that being used instead of random numbers in Monte Carlo algorithms imply their convergence in the classical sense, efficient mainly for algorithms with small constructive dimensions.
139 citations
TL;DR: This work reviews and discusses some recent progress in the theory of Markov-chain Monte Carlo applications and attempts to assess the relevance of this theory for practical applications.
Abstract: We review and discuss some recent progress in the theory of Markov-chain Monte Carlo applications, particularly oriented to applications in statistics. We attempt to assess the relevance of this theory for practical applications.
139 citations