Home > Publications database > TopSuite Web Server: A Meta-Suite for Deep-Learning-Based Protein Structure and Quality Prediction |
Journal Article | FZJ-2021-00457 |
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2021
American Chemical Society64160
Washington, DC
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Please use a persistent id in citations: http://hdl.handle.net/2128/27236 doi:10.1021/acs.jcim.0c01202
Abstract: Proteins carry out the most fundamental processes of life such as cellular metabolism, regulation, and communication. Understanding these processes at a molecular level requires knowledge of their three-dimensional structures. Experimental techniques such as X-ray crystallography, NMR spectroscopy, and cryogenic electron microscopy can resolve protein structures but are costly and time-consuming and do not work for all proteins. Computational protein structure prediction tries to overcome these problems by predicting the structure of a new protein using existing protein structures as a resource. Here we present TopSuite, a web server for protein model quality assessment (TopScore) and template-based protein structure prediction (TopModel). TopScore provides meta-predictions for global and residue-wise model quality estimation using deep neural networks. TopModel predicts protein structures using a top-down consensus approach to aid the template selection and subsequently uses TopScore to refine and assess the predicted structures. The TopSuite Web server is freely available at https://cpclab.uni-duesseldorf.de/topsuite/.
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