Conformational Ensembles from Experimental Data and Computer Simulations

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Conformational Ensembles from Experimental Data
and Computer Simulations Poster Abstracts
114
79-POS Board 39
Kinetics of RNA Unzipping: Insights from Density-Peak Clustering Applied to Core-set
Markov State Models
Giovanni Pinamonti2,1, Fabian Paul2, Frank Noe2, Alessandro Laio1, Giovanni Bussi 1.
1International School for Advanced Studies, SISSA, Trieste, Italy, 2Freie Universitaet, Berlin,
Germany.
We present a novel approach to the construction of a Markov state model that describes the
dynamics of a biomolecular system, starting from atomistic MD simulations. We make use of the
unsupervised density peak (UDP) clustering algorithm, introduced by Rodriguez and Laio [2014]
and further developed by d’Errico et al. [2017]. We combine this algorithm with time-lagged
independent component analysis (TICA) [Molgedey and Schuster, 1994] in order to define the
microstates of the system and we next compute the transition probabilities between them using a
“core-set approach” [Buchete and Hummer, 2008]. We test this approach by studying the process
of the fraying of the terminal base pair in a RNA double helix, characterizing the different
pathways involved and the sequence dependence of the process timescales.