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Modeling complexes of modeled proteins
- Source :
- Proteins: Structure, Function, and Bioinformatics. 85:470-478
- Publication Year :
- 2016
- Publisher :
- Wiley, 2016.
-
Abstract
- Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such “double” modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 A Cα RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5 – 6 A RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 A. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. This article is protected by copyright. All rights reserved.
- Subjects :
- 0301 basic medicine
Protein structure prediction
Biology
Biochemistry
Interactome
03 medical and health sciences
Crystallography
030104 developmental biology
Molecular level
Protein–ligand docking
Structural Biology
Docking (molecular)
Protein model
Protein recognition
Macromolecular docking
Biological system
Molecular Biology
Subjects
Details
- ISSN :
- 08873585
- Volume :
- 85
- Database :
- OpenAIRE
- Journal :
- Proteins: Structure, Function, and Bioinformatics
- Accession number :
- edsair.doi...........2dc79fb8ba15c1f16e20f4cba663a170
- Full Text :
- https://doi.org/10.1002/prot.25183