Subtle Monte Carlo Updates in Dense Molecular Systems

Sandro Bottaro, Wouter Boomsma, Kristoffer E. Johansson, Christian Andreetta, Thomas Hamelryck, Jesper Ferkinghoff-Borg

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results suggest our method as a valuable tool in the study of molecules in atomic detail, offering a potential alternative to molecular dynamics for probing long time-scale conformational transitions.
Original languageEnglish
JournalJournal of Chemical Theory and Computation
Volume8
Issue number2
Pages (from-to)695-702
ISSN1549-9618
DOIs
Publication statusPublished - 2012

Keywords

  • CHEMISTRY
  • PHYSICS
  • PROTEIN-STRUCTURE
  • CONFORMATIONAL ENSEMBLES
  • NMR RELAXATION
  • DYNAMICS
  • SIMULATION
  • UBIQUITIN
  • BIAS
  • BOND
  • RECOGNITION
  • PARAMETERS

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