Search from over 60,000 research works

Advanced Search

IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences

[thumbnail of Open Access]
Preview
NAR_2015_IntFOLD_Published.pdf - Published Version (3MB) | Preview
Available under license: Creative Commons Attribution
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

McGuffin, L. J. orcid id iconORCID: https://orcid.org/0000-0003-4501-4767, Atkins, J. D., Salehe, B. R., Shuid, A. N. and Roche, D. B. (2015) IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences. Nucleic Acids Research, 43 (W1). W169-W173. ISSN 1362-4962 doi: 10.1093/nar/gkv236

Abstract/Summary

IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at: http://www.reading.ac.uk/bioinf/IntFOLD/

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/39867
Item Type Article
Refereed Yes
Divisions Interdisciplinary centres and themes > Institute for Cardiovascular and Metabolic Research (ICMR)
Life Sciences > School of Biological Sciences > Biomedical Sciences
Publisher Oxford University Press
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar