Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data and Computer Simulations

Poster Abstracts

79-POS Board 39 Kinetics of RNA Unzipping: Insights from Density-Peak Clustering Applied to Core-set Markov State Models Giovanni Pinamonti 2,1 , Fabian Paul 2 , Frank Noe 2 , Alessandro Laio 1 , Giovanni Bussi 1 . 1 International School for Advanced Studies, SISSA, Trieste, Italy, 2 Freie 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.

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