Prediction of Protein Structure Using Surface Accessibility Data.
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ABSTRACT:
SUBMITTER: Hartlmuller C
PROVIDER: S-EPMC5026166 | biostudies-literature | 2016 Sep
REPOSITORIES: biostudies-literature
Publications
Prediction of Protein Structure Using Surface Accessibility Data.
Hartlmüller Christoph C Göbl Christoph C Madl Tobias T
Angewandte Chemie (International ed. in English) 20160825 39
An approach to the de novo structure prediction of proteins is described that relies on surface accessibility data from NMR paramagnetic relaxation enhancements by a soluble paramagnetic compound (sPRE). This method exploits the distance-to-surface information encoded in the sPRE data in the chemical shift-based CS-Rosetta de novo structure prediction framework to generate reliable structural models. For several proteins, it is demonstrated that surface accessibility data is an excellent measure ...[more]
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