Assessing protein conformational landscapes: integration of DEER data in Maximum Occurrence analysis

The properties of the conformational landscape of a biomolecule are of capital importance to understand its function. It is widely accepted that a statistical ensemble is far more representative than a single structure, especially for proteins with disordered regions. While experimental data provide...

Full description

Saved in:
Bibliographic Details
Published in:Physical chemistry chemical physics : PCCP 2018-11, Vol.20 (43), p.27429-27438
Main Authors: Gigli, Lucia, Andrałojć, Witold, Dalaloyan, Arina, Parigi, Giacomo, Ravera, Enrico, Goldfarb, Daniella, Luchinat, Claudio
Format: Article
Language:English
Subjects:
Calcium - metabolism
Calcium ions
Calmodulin
Calmodulin - chemistry
Landscape
Magnetic Resonance Spectroscopy
NMR
Nuclear magnetic resonance
Protein Conformation
Proteins
Scattering, Small Angle
Small angle X ray scattering
Spin Labels
Upper bounds
Weight
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The properties of the conformational landscape of a biomolecule are of capital importance to understand its function. It is widely accepted that a statistical ensemble is far more representative than a single structure, especially for proteins with disordered regions. While experimental data provide the most important handle on the conformational variability that the system is experiencing, they usually report on either time or ensemble averages. Since the available conformations largely outnumber the (independent) available experimental data, the latter can be equally well reproduced by a variety of ensembles. We have proposed the Maximum Occurrence (MaxOcc) approach to provide an upper bound of the statistical weight of each conformation. This method is expected to converge towards the true statistical weights by increasing the number of independent experimental datasets. In this paper we explore the ability of DEER (Double Electron Electron Resonance) data, which report on the distance distribution between two spin labels attached to a biomolecule, to restrain the MaxOcc values and its complementarity to previously introduced experimental techniques such as NMR and Small-Angle X-ray Scattering. We here present the case of Ca2+ bound calmodulin (CaM) as a test case and show that DEER data impose a sizeable reduction of the conformational space described by high MaxOcc conformations.
ISSN:1463-9076
1463-9084
DOI:10.1039/c8cp06195e