Journal article
UniAlign: protein structure alignment meets evolution
Bioinformatics (Oxford, England), v 31(19), pp 3139-3146
01 Oct 2015
PMID: 26059715
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
During the evolution, functional sites on the surface of the protein as well as the hydrophobic core maintaining the structural integrity are well-conserved. However, available protein structure alignment methods align protein structures based solely on the 3D geometric similarity, limiting their ability to detect functionally relevant correspondences between the residues of the proteins, especially for distantly related homologous proteins.
In this article, we propose a new protein pairwise structure alignment algorithm (UniAlign) that incorporates additional evolutionary information captured in the form of sequence similarity, sequence profiles and residue conservation. We define a per-residue score (UniScore) as a weighted sum of these and other features and develop an iterative optimization procedure to search for an alignment with the best overall UniScore. Our extensive experiments on CDD, HOMSTRAD and BAliBASE benchmark datasets show that UniAlign outperforms commonly used structure alignment methods. We further demonstrate UniAlign's ability to develop family-specific models to drastically improve the quality of the alignments.
UniAlign is available as a web service at: http://sacan.biomed.drexel.edu/unialign
ahmet.sacan@drexel.edu
Supplementary data are available at Bioinformatics online.
Metrics
Details
- Title
- UniAlign: protein structure alignment meets evolution
- Creators
- Chunyu Zhao - Center for Integrated Bioinformatics, School of Biomedical Engineering, Science and Health System, Drexel University, Philadelphia, PA 19104, USAAhmet Sacan - Center for Integrated Bioinformatics, School of Biomedical Engineering, Science and Health System, Drexel University, Philadelphia, PA 19104, USA
- Publication Details
- Bioinformatics (Oxford, England), v 31(19), pp 3139-3146
- Publisher
- Oxford University Press; England
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000362845400009
- Scopus ID
- 2-s2.0-84943403629
- Other Identifier
- 991014877949904721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Biochemical Research Methods
- Biotechnology & Applied Microbiology
- Computer Science, Interdisciplinary Applications
- Mathematical & Computational Biology
- Statistics & Probability