Simultaneous Alignment and Folding of Protein Sequences
Name
Devadas_Simultaneous alignment.pdf
Size
399.77 KB
Format
Adobe PDF
Checksum (MD5)
6e237174d9e1859812bf3f35a6de6797
Author(s)
O'Donnell, Charles William
Will, Sebastian
Devadas, Srinivas
Backofen, Rolf
Berger, Bonnie
Waldispuhl, Jerome
Date Issued
April 2014
Journal
Journal of Computational Biology
Publisher
Mary Ann Liebert
Citation
Waldispuhl, Jerome, Charles W. O’Donnell, Sebastian Will, Srinivas Devadas, Rolf Backofen, and Bonnie Berger. “Simultaneous Alignment and Folding of Protein Sequences.” Journal of Computational Biology 21, no. 7 (July 2014): 477–491. © Mary Ann Liebert, Inc.
Version
Final published version
Abstract
Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We present partiFold-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 and multiple sequence alignment tools in the most difficult low-sequence homology case. It also 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/).
MIT Department
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
Massachusetts Institute of Technology. Research Laboratory of Electronics
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1089/cmb.2013.0163
