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ModFOLD8: accurate global and local quality estimates for 3D protein models

McGuffin, L. J. ORCID: https://orcid.org/0000-0003-4501-4767, Aldowsari, F. M. F., Alharbi, S. M. A. and Adiyaman, R. (2022) ModFOLD8: accurate global and local quality estimates for 3D protein models. Nucleic Acids Research, 49 (W1). W425-W430. ISSN 1362-4962

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To link to this item DOI: 10.1093/nar/gkab321

Abstract/Summary

Methods for estimating the quality of 3D models of proteins are vital tools for driving the acceptance and utility of predicted tertiary structures by the wider bioscience community. Here we describe the significant major updates to ModFOLD, which has maintained its position as a leading server for the prediction of global and local quality of 3D protein models, over the past decade (>20 000 unique external users). ModFOLD8 is the latest version of the server, which combines the strengths of multiple pure-single and quasi-single model methods. Improvements have been made to the web server interface and there has been successive increases in prediction accuracy, which were achieved through integration of newly developed scoring methods and advanced deep learning-based residue contact predictions. Each version of the ModFOLD server has been independently blind tested in the biennial CASP experiments, as well as being continuously evaluated via the CAMEO project. In CASP13 and CASP14, the ModFOLD7 and ModFOLD8 variants ranked among the top 10 quality estimation methods according to almost every official analysis. Prior to CASP14, ModFOLD8 was also applied for the evaluation of SARS-CoV-2 protein models as part of CASP Commons 2020 initiative. The ModFOLD8 server is freely available at: https://www.reading.ac.uk/bioinf/ModFOLD/.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Institute for Cardiovascular and Metabolic Research (ICMR)
Interdisciplinary centres and themes > Reading Systems Biology Network (RSBN)
Life Sciences > School of Biological Sciences > Biomedical Sciences
ID Code:97498
Publisher:Oxford University Press

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