| Literature DB >> 24766258 |
Jérôme Waldispühl1, Charles W O'Donnell, Sebastian Will, Srinivas Devadas, Rolf Backofen, Bonnie Berger.
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/ ).Mesh:
Substances:
Year: 2014 PMID: 24766258 PMCID: PMC4082353 DOI: 10.1089/cmb.2013.0163
Source DB: PubMed Journal: J Comput Biol ISSN: 1066-5277 Impact factor: 1.479