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ModFOLD6: an accurate web server for the global and local quality estimation of 3D protein models

Maghrabi, A. H. A. and McGuffin, L. J. (2017) ModFOLD6: an accurate web server for the global and local quality estimation of 3D protein models. Nucleic Acids Research, 45 (W1). W416-W421. ISSN 0305-1048

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To link to this item DOI: 10.1093/nar/gkx332

Abstract/Summary

Methods that reliably estimate the likely similarity between the predicted and native structures of proteins have become essential for driving the acceptance and adoption of three-dimensional protein models by life scientists. ModFOLD6 is the latest version of our leading resource for Estimates of Model Accuracy (EMA), which uses a pioneering hybrid quasi-single model approach. The ModFOLD6 server integrates scores from three pure-single model methods and three quasi-single model methods using a neural network to estimate local quality scores. Additionally, the server provides three options for producing global score estimates, depending on the requirements of the user: (i) ModFOLD6_rank, which is optimized for ranking/selection, (ii) ModFOLD6_cor, which is optimized for correlations of predicted and observed scores and (iii) ModFOLD6 global for balanced performance. The ModFOLD6 methods rank among the top few for EMA, according to independent blind testing by the CASP12 assessors. The ModFOLD6 server is also continuously automatically evaluated as part of the CAMEO project, where significant performance gains have been observed compared to our previous server and other publicly available servers. The ModFOLD6 server is freely available at: http://www.reading.ac.uk/bioinf/ModFOLD/.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Food Chain and Health
Interdisciplinary centres and themes > Institute for Cardiovascular and Metabolic Research (ICMR)
Interdisciplinary centres and themes > Reading Systems Biology Network (RSBN)
Faculty of Life Sciences > School of Biological Sciences > Biomedical Sciences
ID Code:70267
Publisher:Oxford University Press

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