Efficient Computation, Sensitivity and Error Analysis of Committor Probabilities for Complex Dynamical Processes
Please always quote using this URN:urn:nbn:de:0296-matheon-11034
- In many fields of physics, chemistry and biology the characterization of dynamical processes between states or species is of fundamental interest. The central mathematical function in such sit- uations is the committor probability - a generalized reaction coordinate that measures the progress of the process of interest as the probability of proceeding towards the target state rather than re- lapsing to the source state. Here, we present methodology for the efficient computation of com- mittor probabilities for large-scale systems, such as, for example simuations of biomolecular fold- ing. A method is derived for computing the committor for discrete state spaces using eigenvectors with expressions for the sensitivity and a Bayesian error model for the committor. The concepts are illustrated on two examples of diffusive dynamics with a very large number of states: a two- dimensional model potential with three minima, and a three-dimensional model representing protein-ligand binding. The method can finally be used to compute committor probabilities in- cluding error estimations for medium and large system sizes allowing access to the apparatus of transition path theory and its applications.
Author: | Jan-Hendrik Prinz, Martin Held, Jeremy C. Smith, Frank Noe |
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URN: | urn:nbn:de:0296-matheon-11034 |
Referee: | Christof Schütte |
Document Type: | Preprint, Research Center Matheon |
Language: | English |
Date of first Publication: | 2012/05/18 |
Release Date: | 2012/05/18 |
Institute: | Research Center Matheon |
Freie Universität Berlin | |
MSC-Classification: | 62-XX STATISTICS / 62Mxx Inference from stochastic processes / 62M05 Markov processes: estimation |
Preprint Number: | 959 |