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UniAlign: protein structure alignment meets evolution
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| Zeitschriftentitel: | Bioinformatics |
|---|---|
| Personen und Körperschaften: | , |
| In: | Bioinformatics, 31, 2015, 19, S. 3139-3146 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Oxford University Press (OUP)
|
| Schlagwörter: |
| author_facet |
Zhao, Chunyu Sacan, Ahmet Zhao, Chunyu Sacan, Ahmet |
|---|---|
| author |
Zhao, Chunyu Sacan, Ahmet |
| spellingShingle |
Zhao, Chunyu Sacan, Ahmet Bioinformatics UniAlign: protein structure alignment meets evolution Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability |
| author_sort |
zhao, chunyu |
| spelling |
Zhao, Chunyu Sacan, Ahmet 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/btv354 <jats:title>Abstract</jats:title> <jats:p>Motivation: 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.</jats:p> <jats:p>Results: 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.</jats:p> <jats:p>Availability and implementation: UniAlign is available as a web service at: http://sacan.biomed.drexel.edu/unialign</jats:p> <jats:p>Contact: ahmet.sacan@drexel.edu</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> UniAlign: protein structure alignment meets evolution Bioinformatics |
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10.1093/bioinformatics/btv354 |
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UniAlign: protein structure alignment meets evolution |
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UniAlign: protein structure alignment meets evolution |
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UniAlign: protein structure alignment meets evolution |
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UniAlign: protein structure alignment meets evolution |
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UniAlign: protein structure alignment meets evolution |
| title_short |
UniAlign: protein structure alignment meets evolution |
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unialign: protein structure alignment meets evolution |
| topic |
Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability |
| url |
http://dx.doi.org/10.1093/bioinformatics/btv354 |
| publishDate |
2015 |
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3139-3146 |
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<jats:title>Abstract</jats:title>
<jats:p>Motivation: 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.</jats:p>
<jats:p>Results: 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.</jats:p>
<jats:p>Availability and implementation: UniAlign is available as a web service at: http://sacan.biomed.drexel.edu/unialign</jats:p>
<jats:p>Contact: ahmet.sacan@drexel.edu</jats:p>
<jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> |
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| author | Zhao, Chunyu, Sacan, Ahmet |
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| description | <jats:title>Abstract</jats:title> <jats:p>Motivation: 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.</jats:p> <jats:p>Results: 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.</jats:p> <jats:p>Availability and implementation: UniAlign is available as a web service at: http://sacan.biomed.drexel.edu/unialign</jats:p> <jats:p>Contact: ahmet.sacan@drexel.edu</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> |
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| spelling | Zhao, Chunyu Sacan, Ahmet 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/btv354 <jats:title>Abstract</jats:title> <jats:p>Motivation: 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.</jats:p> <jats:p>Results: 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.</jats:p> <jats:p>Availability and implementation: UniAlign is available as a web service at: http://sacan.biomed.drexel.edu/unialign</jats:p> <jats:p>Contact: ahmet.sacan@drexel.edu</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> UniAlign: protein structure alignment meets evolution Bioinformatics |
| spellingShingle | Zhao, Chunyu, Sacan, Ahmet, Bioinformatics, UniAlign: protein structure alignment meets evolution, Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability |
| title | UniAlign: protein structure alignment meets evolution |
| title_full | UniAlign: protein structure alignment meets evolution |
| title_fullStr | UniAlign: protein structure alignment meets evolution |
| title_full_unstemmed | UniAlign: protein structure alignment meets evolution |
| title_short | UniAlign: protein structure alignment meets evolution |
| title_sort | unialign: protein structure alignment meets evolution |
| title_unstemmed | UniAlign: protein structure alignment meets evolution |
| topic | Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability |
| url | http://dx.doi.org/10.1093/bioinformatics/btv354 |