A Random Force is a Force, of Course, of Coarse: Decomposing Complex Enzyme Kinetics with Surrogate Models

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dc.contributor.authorCalderon, Christopher P.
dc.date.accessioned2018-06-19T17:45:08Z
dc.date.available2018-06-19T17:45:08Z
dc.date.issued2009-06
dc.date.noteJune 2009
dc.description.abstractThe temporal autocorrelation (AC) function associated with monitoring order parameters characterizing conformational fluctuations of an enzyme is analyzed using a collection of surrogate models. The surrogates considered are phenomenological stochastic differential equation (SDE) models. It is demonstrated how an ensemble of such surrogate models, each surrogate being calibrated from a single trajectory, indirectly contains information about unresolved conformational degrees of freedom. This ensemble can be used to construct complex temporal ACs associated with a ``non-Markovian" process. The ensemble of surrogates approach allows researchers to consider models more flexible than a mixture of exponentials to describe relaxation times and at the same time gain physical information about the system. The relevance of this type of analysis to matching single-molecule experiments to computer simulations and how more complex stochastic processes can emerge from a mixture of simpler processes is also discussed. The ideas are illustrated on a toy SDE model and on molecular dynamics simulations of the enzyme dihydrofolate reductase.
dc.format.extent11 pp
dc.identifier.citationCalderon, Christopher P.. "A Random Force is a Force, of Course, of Coarse: Decomposing Complex Enzyme Kinetics with Surrogate Models." (2009) <a href="https://hdl.handle.net/1911/102126">https://hdl.handle.net/1911/102126</a>.
dc.identifier.digitalTR09-22
dc.identifier.urihttps://hdl.handle.net/1911/102126
dc.language.isoeng
dc.titleA Random Force is a Force, of Course, of Coarse: Decomposing Complex Enzyme Kinetics with Surrogate Models
dc.typeTechnical report
dc.type.dcmiText
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