Data-driven models for protein interaction and design

Data-driven models for protein interaction and design

ABSTRACT We describe methods and results for four new types of challenge in the Critical Assessment of PRedicted Interactions (CAPRI). Two new challenges asked predictors to create models related to protein interface design. The first of these was to distinguish binding interfaces from designed nonb...

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Veröffentlicht in:Proteins, structure, function, and bioinformatics structure, function, and bioinformatics, 2013-12, Vol.81 (12), p.2221-2228
Hauptverfasser: Zhu, Xiaolei, Ericksen, Spencer S., Demerdash, Omar N. A., Mitchell, Julie C.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Artificial Intelligence
binding prediction
Bioinformatics
Crystallography, X-Ray
Hemagglutinins - chemistry
Heparin - chemistry
heparin binding
machine learning
Models, Molecular
Molecular Docking Simulation
Mutagenesis
Point Mutation
Protein Binding
Protein Conformation
protein interaction
Protein Interaction Maps
Software
Water - chemistry
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Zusammenfassung:ABSTRACT We describe methods and results for four new types of challenge in the Critical Assessment of PRedicted Interactions (CAPRI). Two new challenges asked predictors to create models related to protein interface design. The first of these was to distinguish binding interfaces from designed nonbinding interfaces. The second was to predict the effects of all single‐point mutations on hemagglutinin binding to two small designed proteins. Two additional challenges asked predictors to submit high‐resolution structures for interface‐bound crystallographic waters and for binding heparin to a putative glycosylase. Proteins 2013; 81:2221–2228. © 2013 Wiley Periodicals, Inc.
ISSN:0887-3585
1097-0134
DOI:10.1002/prot.24405