SCORE: Predicting the core of protein models

Deane, Charlotte M., Kaas, Quentin and Blundell, Tom L. (2001) SCORE: Predicting the core of protein models. Bioinformatics, 17 6: 541-550. doi:10.1093/bioinformatics/17.6.541


Author Deane, Charlotte M.
Kaas, Quentin
Blundell, Tom L.
Title SCORE: Predicting the core of protein models
Journal name Bioinformatics   Check publisher's open access policy
ISSN 1367-4811
1367-4803
Publication date 2001-06
Sub-type Article (original research)
DOI 10.1093/bioinformatics/17.6.541
Volume 17
Issue 6
Start page 541
End page 550
Total pages 10
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Formatted abstract
Motivation: The prediction of the regions of homology models that can be 'restrained by' or 'copied from' the basis structures is a vital step in correct model generation, because these regions are the models most accurate part. However, there is no ideal method for the identification of their limits. In most algorithms their length depends on the number of family members and definitions of secondary structure.
Results: The algorithm SCORE steps away from the conventional definitions of the core to identify from large numbers of basis structures those regions that can be considered structurally related to a target sequence. The use of φ, ψ constraints to accurately pinpoint the regions that are conserved across a family and environmentally constrained substitution tables to extend these regions allows SCORE to rapidly (generally in under 1 s, an order of magnitude faster than methods such as MODELLER) identify and build the core of homology models from the alignments of the target sequence to the basis structures. The SCORE algorithm was used to build 114 model cores. In only two cases was the core size less than 50% of the structure and all the cores built had an RMSD of 3.7 A or less to the target structure.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Institute for Molecular Bioscience - Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 12 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Fri, 03 Dec 2010, 10:04:28 EST by Dr Quentin Kaas on behalf of Institute for Molecular Bioscience