ausblenden:
Schlagwörter:
Ensemble refinement; Bayes; Maximum entropy; Minimal ensemble
Zusammenfassung:
The flexible and dynamic nature of biomolecules and biomolecular complexes is essential for many cellularfunctions in living organisms but poses a challenge for experimental methods to determine high-resolutionstructural models. To meet this challenge, experiments are combined with molecular simulations. The latterpropose models for structural ensembles, and the experimental data can be used to steer these simulationsand to select ensembles that most likely underlie the experimental data. Here, we explain in detail how the“Bayesian Inference Of ENsembles” (BioEn) method can be used to refine such ensembles using a widerange of experimental data. The “Ensemble Refinement of SAXS” (EROS) method is a special case ofBioEn, inspired by the Gull-Daniell formulation of maximum entropy image processing and focusedoriginally on X-ray solution scattering experiments (SAXS) and then extended to integrative structuralmodeling. We also briefly sketch the “minimum ensemble method,” a maximum-parsimony refinementmethod that seeks to represent an ensemble with a minimal number of representative structures.
