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Link to original content: http://www.ncbi.nlm.nih.gov/pubmed/25797794
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Review
. 2015 Nov;16(6):1025-34.
doi: 10.1093/bib/bbv009. Epub 2015 Mar 21.

Predicting protein interface residues using easily accessible on-line resources

Surabhi Maheshwari, Michal Brylinski
Review

Predicting protein interface residues using easily accessible on-line resources

Surabhi Maheshwari et al. Brief Bioinform. 2015 Nov.

Abstract

It has been more than a decade since the completion of the Human Genome Project that provided us with a complete list of human proteins. The next obvious task is to figure out how various parts interact with each other. On that account, we review 10 methods for protein interface prediction, which are freely available as web servers. In addition, we comparatively evaluate their performance on a common data set comprising different quality target structures. We find that using experimental structures and high-quality homology models, structure-based methods outperform those using only protein sequences, with global template-based approaches providing the best performance. For moderate-quality models, sequence-based methods often perform better than those structure-based techniques that rely on fine atomic details. We note that post-processing protocols implemented in several methods quantitatively improve the results only for experimental structures, suggesting that these procedures should be tuned up for computer-generated models. Finally, we anticipate that advanced meta-prediction protocols are likely to enhance interface residue prediction. Notwithstanding further improvements, easily accessible web servers already provide the scientific community with convenient resources for the identification of protein-protein interaction sites.

Keywords: interfacial residues; protein interface prediction; protein models; protein–protein complexes; protein–protein interactions; web servers.

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Figures

Figure 1.
Figure 1.
ROC plots assessing the accuracy of interface residue prediction by 10 web servers across three BM90 data sets. (A) Crystal structures, BM90C; (B) high-quality models, BM90H; and (C) moderate-quality models, BM90M. Continuous ROC lines are calculated using raw residue scores with triangles corresponding to the best performance of raw scores. Default predictions by web servers, including post-processing, are shown as diamonds and circles; circles are used for those web servers that do not provide continuous residue scores. Asterisks mark the accuracy of a pseudo-meta approach that combines the best predictions produced by individual algorithms.
See this image and copyright information in PMC

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