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Hybrid Monte Carlo with Adaptive Temperature in a Mixed-Canonical Ensemble: Efficient Conformational Analysis of RNA

Please always quote using this URN: urn:nbn:de:0297-zib-3364
  • A hybrid Monte Carlo method with adaptive temperature choice is presented, which exactly generates the distribution of a mixed-canonical ensemble composed of two canonical ensembles at low and high temperature. The analysis of resulting Markov chains with the reweighting technique shows an efficient sampling of the canonical distribution at low temperature, whereas the high temperature component facilitates conformational transitions, which allows shorter simulation times. \\The algorithm was tested by comparing analytical and numerical results for the small n-butane molecule before simulations were performed for a triribonucleotide. Sampling the complex multi-minima energy landscape of these small RNA segments, we observed enforced crossing of energy barriers.

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Author:Alexander Fischer, Frank Cordes, Christof Schütte
Document Type:ZIB-Report
Date of first Publication:1997/12/17
Series (Serial Number):ZIB-Report (SC-97-67)
Published in:Appeared in: Journal of Computational Chemistry Vol. 19, No. 15 (1998) pp. 1689-1697
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