English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Detection of protein catalytic residues at high precision using local network properties

Slama, P., Filippis, I., & Lappe, M. (2008). Detection of protein catalytic residues at high precision using local network properties. BMC Bioinformatics, 9, 517-517. doi:10.1186/1471-2105-9-517.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7E8F-D Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7E90-7
Genre: Journal Article
Alternative Title : BMC Bioinformatics

Files

show Files
hide Files
:
1471-2105-9-517.pdf (Any fulltext), 1020KB
Name:
1471-2105-9-517.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
eDoc_access: PUBLIC
License:
-

Locators

show

Creators

show
hide
 Creators:
Slama, Patrick1, Author
Filippis, Ioannis1, Author
Lappe, Michael2, Author              
Affiliations:
1Max Planck Society, ou_persistent13              
2Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433554              

Content

show
hide
Free keywords: -
 Abstract: BACKGROUND: Identifying the active site of an enzyme is a crucial step in functional studies. While protein sequences and structures can be experimentally characterized, determining which residues build up an active site is not a straightforward process. In the present study a new method for the detection of protein active sites is introduced. This method uses local network descriptors derived from protein three-dimensional structures to determine whether a residue is part of an active site. It thus does not involve any sequence alignment or structure similarity to other proteins. A scoring function is elaborated over a set of more than 220 proteins having different structures and functions, in order to detect protein catalytic sites with a high precision, i.e. with a minimal rate of false positives. RESULTS: The scoring function was based on the counts of first-neighbours on side-chain contacts, third-neighbours and residue type. Precision of the detection using this function was 28.1%, which represents a more than three-fold increase compared to combining closeness centrality with residue surface accessibility, a function which was proposed in recent years. The performance of the scoring function was also analysed into detail over a smaller set of eight proteins. For the detection of 'functional' residues, which were involved either directly in catalytic activity or in the binding of substrates, precision reached a value of 72.7% on this second set. These results suggested that our scoring function was effective at detecting not only catalytic residues, but also any residue that is part of the functional site of a protein. CONCLUSION: As having been validated on the majority of known structural families, this method should prove useful for the detection of active sites in any protein with unknown function, and for direct application to the design of site-directed mutagenesis experiments.

Details

show
hide
Language(s): eng - English
 Dates: 2008-12-04
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: BMC Bioinformatics
  Alternative Title : BMC Bioinformatics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 9 Sequence Number: - Start / End Page: 517 - 517 Identifier: -