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Ensemble models of proteins and protein domains based on distance distribution restraints
Author(s) -
Jeschke Gunnar
Publication year - 2016
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.25000
Subject(s) - dihedral angle , conformational ensembles , monte carlo method , intrinsically disordered proteins , electron paramagnetic resonance , statistical physics , protein structure , chemistry , chemical physics , site directed spin labeling , dipole , molecular dynamics , crystallography , physics , biological system , nuclear magnetic resonance , computational chemistry , molecule , mathematics , biology , hydrogen bond , statistics , organic chemistry
Conformational ensembles of intrinsically disordered peptide chains are not fully determined by experimental observations. Uncertainty due to lack of experimental restraints and due to intrinsic disorder can be distinguished if distance distributions restraints are available. Such restraints can be obtained from pulsed dipolar electron paramagnetic resonance (EPR) spectroscopy applied to pairs of spin labels. Here, we introduce a Monte Carlo approach for generating conformational ensembles that are consistent with a set of distance distribution restraints, backbone dihedral angle statistics in known protein structures, and optionally, secondary structure propensities or membrane immersion depths. The approach is tested with simulated restraints for a terminal and an internal loop and for a protein with 69 residues by using sets of sparse restraints for underlying well‐defined conformations and for published ensembles of a premolten globule‐like and a coil‐like intrinsically disordered protein. Proteins 2016; 84:544–560. © 2016 Wiley Periodicals, Inc.