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Refinement of Highly Flexible Protein Structures using Simulation‐Guided Spectroscopy
Author(s) -
Hays Jennifer M.,
Kieber Marissa K.,
Li Jason Z.,
Han Ji In,
Columbus Linda,
Kasson Peter M.
Publication year - 2018
Publication title -
angewandte chemie
Language(s) - English
Resource type - Journals
eISSN - 1521-3757
pISSN - 0044-8249
DOI - 10.1002/ange.201810462
Subject(s) - conformational ensembles , limiting , underdetermined system , protein structure , computer science , molecular dynamics , function (biology) , biological system , molecular conformation , chemistry , selection (genetic algorithm) , computational chemistry , algorithm , machine learning , molecule , biology , biochemistry , mechanical engineering , organic chemistry , evolutionary biology , engineering
Highly flexible proteins present a special challenge for structure determination because they are multi‐structured yet not disordered, so their conformational ensembles are essential for understanding function. Because spectroscopic measurements of multiple conformational populations often provide sparse data, experiment selection is a limiting factor in conformational refinement. A molecular simulations‐ and information‐theory based approach to select which experiments best refine conformational ensembles has been developed. This approach was tested on three flexible proteins. For proteins where a clear mechanistic hypothesis exists, experiments that test this hypothesis were systematically identified. When available data did not yield such mechanistic hypotheses, experiments that significantly outperform structure‐guided approaches in conformational refinement were identified. This approach offers a particular advantage when refining challenging, underdetermined protein conformational ensembles.