Inference of structure ensembles of flexible biomolecules from sparse, averaged data.
We present the theoretical foundations of a general principle to infer structure ensembles of flexible biomolecules from spatially and temporally averaged data obtained in biophysical experiments. The central idea is to compute the Kullback-Leibler optimal modification of a given prior distribution τ(x) with respect to the experimental data and its uncertainty. This principle generalizes the successful inferential structure determination method and recently proposed maximum entropy methods. Tractability of the protocol is demonstrated through the analysis of simulated nuclear magnetic resonance spectroscopy data of a small peptide.
Bioinformatics Centre, Department of Biology, Faculty of Science, University of Copenhagen, Copenhagen, Denmark.
Simon
S
Olsson
Jes
J
Frellsen
Wouter
W
Boomsma
Kanti V
KV
Mardia
Thomas
T
Hamelryck
D000465:Algorithms; D001703:Biophysics; D003198:Computer Simulation; D008962:Models, Theoretical