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Integrating Molecular Simulation and Experimental Data: A Bayesian/Maximum Entropy Reweighting Approach

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

We describe a Bayesian/Maximum entropy (BME) procedure and software to construct a conformational ensemble of a biomolecular system by integrating molecular simulations and experimental data. First, an initial conformational ensemble is constructed using, for example, Molecular Dynamics or Monte Carlo simulations. Due to potential inaccuracies in the model and finite sampling effects, properties predicted from simulations may not agree with experimental data. In BME we use the experimental data to refine the simulation so that the new conformational ensemble has the following properties: (1) the calculated averages are close to the experimental values taking uncertainty into account and (2) it maximizes the relative Shannon entropy with respect to the original simulation ensemble. The output of this procedure is a set of optimized weights that can be used to calculate other properties and distributions of these. Here, we provide a practical guide on how to obtain and use such weights, how to choose adjustable parameters and discuss shortcomings of the method.

OriginalsprogEngelsk
TitelStructural Bioinformatics : Methods and Protocols
RedaktørerZoltán Gáspári
Antal sider22
ForlagHumana Press
Publikationsdato2020
Sider219-240
ISBN (Trykt)978-1-0716-0269-0
ISBN (Elektronisk)978-1-0716-0270-6
DOI
StatusUdgivet - 2020
NavnMethods in Molecular Biology
Vol/bind2112
ISSN1064-3745

ID: 238000139