Simultaneous alignment and folding of protein sequences
Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We presentpartiFold-Align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein seq...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en_US |
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Springer Berlin Heidelberg
2010
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| Online Access: | http://hdl.handle.net/1721.1/51685 https://orcid.org/0000-0001-8253-7714 https://orcid.org/0000-0002-2724-7228 |
| _version_ | 1826214331973369856 |
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| author | Waldispuhl, Jerome O'Donnell, Charles William Will, Sebastian Devadas, Srinivas Backofen, Rolf Berger, Bonnie |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Waldispuhl, Jerome O'Donnell, Charles William Will, Sebastian Devadas, Srinivas Backofen, Rolf Berger, Bonnie |
| author_sort | Waldispuhl, Jerome |
| collection | MIT |
| description | Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We presentpartiFold-Align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein sequences; the algorithm’s complexity is polynomial in time and space. Algorithmically,partiFold-Align exploits sparsity in the set of super-secondary structure pairings and alignment candidates to achieve an effectively cubic running time for simultaneous pairwise alignment and folding. We demonstrate the efficacy of these techniques on transmembrane β-barrel proteins, an important yet difficult class of proteins with few known three-dimensional structures. Testing against structurally derived sequence alignments,partiFold-Align significantly outperforms state-of-the-art pairwise sequence alignment tools in the most difficult low sequence homology case and improves secondary structure prediction where current approaches fail. Importantly, partiFold-Align requires no prior training. These general techniques are widely applicable to many more protein families. partiFold-Align is available at http://partiFold.csail.mit.edu. |
| first_indexed | 2024-09-23T16:03:42Z |
| format | Article |
| id | mit-1721.1/51685 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T16:03:42Z |
| publishDate | 2010 |
| publisher | Springer Berlin Heidelberg |
| record_format | dspace |
| spelling | mit-1721.1/516852022-09-29T17:57:17Z Simultaneous alignment and folding of protein sequences Waldispuhl, Jerome O'Donnell, Charles William Will, Sebastian Devadas, Srinivas Backofen, Rolf Berger, Bonnie Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Department of Mathematics Devadas, Srinivas Waldispuhl, Jerome O'Donnell, Charles William Devadas, Srinivas Berger, Bonnie Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We presentpartiFold-Align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein sequences; the algorithm’s complexity is polynomial in time and space. Algorithmically,partiFold-Align exploits sparsity in the set of super-secondary structure pairings and alignment candidates to achieve an effectively cubic running time for simultaneous pairwise alignment and folding. We demonstrate the efficacy of these techniques on transmembrane β-barrel proteins, an important yet difficult class of proteins with few known three-dimensional structures. Testing against structurally derived sequence alignments,partiFold-Align significantly outperforms state-of-the-art pairwise sequence alignment tools in the most difficult low sequence homology case and improves secondary structure prediction where current approaches fail. Importantly, partiFold-Align requires no prior training. These general techniques are widely applicable to many more protein families. partiFold-Align is available at http://partiFold.csail.mit.edu. 2010-02-10T19:12:58Z 2010-02-10T19:12:58Z 2009-05 Article http://purl.org/eprint/type/JournalArticle 1611-3349 0302-9743 http://hdl.handle.net/1721.1/51685 Waldispühl, Jérôme et al. “Simultaneous Alignment and Folding of Protein Sequences.” Research in Computational Molecular Biology 2009. https://orcid.org/0000-0001-8253-7714 https://orcid.org/0000-0002-2724-7228 en_US http://dx.doi.org/10.1007/978-3-642-02008-7_25 Research in Computational Molecular Biology Attribution-Noncommercial-Share Alike 3.0 Unported http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Springer Berlin Heidelberg Srinivas Devadas |
| spellingShingle | Waldispuhl, Jerome O'Donnell, Charles William Will, Sebastian Devadas, Srinivas Backofen, Rolf Berger, Bonnie Simultaneous alignment and folding of protein sequences |
| title | Simultaneous alignment and folding of protein sequences |
| title_full | Simultaneous alignment and folding of protein sequences |
| title_fullStr | Simultaneous alignment and folding of protein sequences |
| title_full_unstemmed | Simultaneous alignment and folding of protein sequences |
| title_short | Simultaneous alignment and folding of protein sequences |
| title_sort | simultaneous alignment and folding of protein sequences |
| url | http://hdl.handle.net/1721.1/51685 https://orcid.org/0000-0001-8253-7714 https://orcid.org/0000-0002-2724-7228 |
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