TY - GEN
T1 - Simultaneous alignment and folding of protein sequences
AU - Waldispühl, Jérǒme
AU - O'Donnell, Charles W.
AU - Will, Sebastian
AU - Devadas, Srinivas
AU - Backofen, Rolf
AU - Berger, Bonnie
PY - 2009/7/17
Y1 - 2009/7/17
N2 - 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 sequence alignment tools in themost 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.
AB - 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 sequence alignment tools in themost 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.
UR - https://www.scopus.com/pages/publications/67650318003
U2 - 10.1007/978-3-642-02008-7_25
DO - 10.1007/978-3-642-02008-7_25
M3 - Conference contribution
AN - SCOPUS:67650318003
SN - 9783642020070
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 339
EP - 355
BT - Research in Computational Molecular Biology - 13th Annual International Conference, RECOMB 2009, Proceedings
T2 - 13th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2009
Y2 - 18 May 2009 through 21 May 2009
ER -