EigenTHREADER: analogous protein fold recognition by efficient contact map threading
- Submitting institution
-
Goldsmiths' College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 3412
- Type
- D - Journal article
- DOI
-
10.1093/bioinformatics/btx217
- Title of journal
- Bioinformatics
- Article number
- -
- First page
- 2684
- Volume
- 33
- Issue
- 17
- ISSN
- 1367-4803
- Open access status
- Technical exception
- Month of publication
- September
- Year of publication
- 2017
- URL
-
http://research.gold.ac.uk/id/eprint/27288/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 17
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- While fold recognition by homology is a solved problem, a substantial number of protein families have no known structural homologues. Yet biochemists still have substantial desire to understand the structural nature of their research proteins when homologues are not available. The paper presents a homology-free method for protein fold recognition. The method demonstrates that a library of protein contact maps (binary matrices) can be searched efficiently by aligning the eigenvectors of contact map pairs. The method is faster than the prior art, AL-Eigen, and outperforms sequence-based fold-recognition methods in the hard task of analogous, non-homologous protein fold detection.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -