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Year: 2013 Volume: 12 Issue: 2

Year: 2013 Volume: 12 Issue: 1

Year: 2012 Volume: 11

Year: 2011 Volume: 10

A critical assessment of information-guided protein-protein docking predictions.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Shih, Edward S. C. Hwang, Ming-Jing
Description	Country affiliation: Taiwan Author Affiliation: Shih ES ( Institute of Biomedical Sciences, Academia Sinica, Nankang, Taipei 115, Taiwan.)
Abstract	The structures of protein complexes are increasingly predicted via protein-protein docking (PPD) using ambiguous interaction data to help guide the docking. These data often are incomplete and contain errors and therefore could lead to incorrect docking predictions. In this study, we performed a series of PPD simulations to examine the effects of incompletely and incorrectly assigned interface residues on the success rate of PPD predictions. The results for a widely used PPD benchmark dataset obtained using a new interface information-driven PPD (IPPD) method developed in this work showed that the success rate for an acceptable top-ranked model varied, depending on the information content used, from as high as 95% when contact relationships (though not contact distances) were known for all residues to 78% when only the interface/non-interface state of the residues was known. However, the success rates decreased rapidly to â¼40% when the interface/non-interface state of 20% of the residues was assigned incorrectly, and to less than 5% for a 40% incorrect assignment. Comparisons with results obtained by re-ranking a global search and with those reported for other data-guided PPD methods showed that, in general, IPPD performed better than re-ranking when the information used was more complete and more accurate, but worse when it was not, and that when using bioinformatics-predicted information on interface residues, IPPD and other data-guided PPD methods performed poorly, at a level similar to simulations with a 40% incorrect assignment. These results provide guidelines for using information about interface residues to improve PPD predictions and reveal a bottleneck for such improvement imposed by the low accuracy of current bioinformatic interface residue predictions.
File Format	HTM / HTML
ISSN	15359476
e-ISSN	15359484
DOI	10.1074/mcp.M112.020198
Journal	Molecular & Cellular Proteomics
Issue Number	3
Volume Number	12
Language	English
Publisher	American Society for Biochemistry and Molecular Biology
Publisher Date	2013-03-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Discipline Proteomics Algorithms Computational Biology Protein Interaction Mapping Proteins Metabolism Binding Sites Computer Simulation Models, Molecular Protein Binding Protein Structure, Tertiary Chemistry Reproducibility Of Results Research Support, Non-u.s. Gov't
Content Type	Text
Resource Type	Article
Subject	Medicine Analytical Chemistry Molecular Biology Biochemistry

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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