Repository: Freie Universität Berlin, Math Department

Predicting the kinetics of RNA oligonucleotides using Markov state models

Pinamonti, G. and Zhao, J. and Condon, D. and Paul, F. and Noé, F. and Turner, D. and Bussi, G. (2017) Predicting the kinetics of RNA oligonucleotides using Markov state models. J. Comp. Theory Comput. , 13 . pp. 926-934.

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Official URL: http://dx.doi.org/10.1021/acs.jctc.6b00982

Abstract

Nowadays different experimental techniques, such as single molecule or relaxation experiments, can provide dynamic properties of biomolecular systems, but the amount of detail obtainable with these methods is often limited in terms of time or spatial resolution. Here we use state-of-the-art computational techniques, namely, atomistic molecular dynamics and Markov state models, to provide insight into the rapid dynamics of short RNA oligonucleotides, to elucidate the kinetics of stacking interactions. Analysis of multiple microsecondlong simulations indicates that the main relaxation modes of such molecules can consist of transitions between alternative folded states, rather than between random coils and native structures. After properly removing structures that are artificially stabilized by known inaccuracies of the current RNA AMBER force field, the kinetic properties predicted are consistent with the time scales of previously reported relaxation experiments.

Item Type:Article
Subjects:Physical Sciences > Chemistry
Mathematical and Computer Sciences
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics > Comp. Molecular Biology
ID Code:1998
Deposited By: BioComp Admin
Deposited On:21 Dec 2016 18:51
Last Modified:27 Jun 2017 15:40

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