Document Detail


Towards the development of standardized methods for comparison, ranking and evaluation of structure alignments.
MedLine Citation:
PMID:  23060612     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
MOTIVATION: Pairwise alignment of protein structures is a fundamental task in structural bioinformatics. There are numerous computer programs in the public domain that produce alignments for a given pair of protein structures, but the results obtained by the various programs generally differ substantially. Hence, in the application of such programs the question arises which of the alignment programs are the most trustworthy in the sense of overall performance, and which programs provide the best result for a given pair of proteins. The major problem in comparing, evaluating and judging alignment results is that there is no clear notion of the optimality of an alignment. As a consequence, the numeric criteria and scores reported by the individual structure alignment programs are largely incomparable.
RESULTS: Here we report on the development and application of a new approach for the evaluation of structure alignment results. The method uses the translation vector and rotation matrix to generate the superposition of two structures but discards the alignment reported by the individual programs. The optimal alignment is then generated in standardized form based on a suitably implemented dynamic programming algorithm where the length of the alignment is the single most informative parameter. We demonstrate that some of the most popular programs in protein structure research differ considerably in their overall performance. In particular, each of the programs investigated here produced in at least in one case the best and the worst alignment compared with all others. Hence, at the current state of development of structure comparison techniques, it is advisable to use several programs in parallel and to choose the optimal alignment in the way reported here.
AVAILABILITY AND IMPLEMENTATION: The computer software that implement the method described here is freely available at http://melolab.org/stovca.
Authors:
Alex W Slater; Javier I Castellanos; Manfred J Sippl; Francisco Melo
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2012-10-11
Journal Detail:
Title:  Bioinformatics (Oxford, England)     Volume:  29     ISSN:  1367-4811     ISO Abbreviation:  Bioinformatics     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2012-12-21     Completed Date:  2013-07-29     Revised Date:  2014-09-22    
Medline Journal Info:
Nlm Unique ID:  9808944     Medline TA:  Bioinformatics     Country:  England    
Other Details:
Languages:  eng     Pagination:  47-53     Citation Subset:  IM    
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Algorithms
Computational Biology / methods,  standards
Models, Molecular
Proteins / chemistry
Software
Structural Homology, Protein*
Grant Support
ID/Acronym/Agency:
P 21294-B12//Austrian Science Fund FWF
Chemical
Reg. No./Substance:
0/Proteins

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Network-based inference from complex proteomic mixtures using SNIPE.
Next Document:  An Ensemble Correlation-Based Gene Selection Algorithm for Cancer Classification with Gene Expressio...