Predicting the Kinetics of RNA Oligonucleotides Using Markov State Models

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• 作者：Giovanni Pinamonti ; Jianbo Zhao ; David E. Condon ; Fabian PaulFrank Noè ; Douglas H. Turner ; Giovanni Bussi
• 刊名：Journal of Chemical Theory and Computation
• 出版年：2017
• 出版时间：February 14, 2017
• 年：2017
• 卷：13
• 期：2
• 页码：926-934
• 全文大小：405K
• ISSN：1549-9626

文摘

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 microsecond-long 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.