PAE viewer: a webserver for the interactive visualization of the predicted aligned error for multimer structure predictions and crosslinks
Abstract The development of AlphaFold for protein structure prediction has opened a new era in structural biology. This is even more the case for AlphaFold-Multimer for the prediction of protein complexes. The interpretation of these predictions has become more important than ever, but it is difficu...
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Veröffentlicht in: | Nucleic acids research 2023-07, Vol.51 (W1), p.W404-W410 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Abstract
The development of AlphaFold for protein structure prediction has opened a new era in structural biology. This is even more the case for AlphaFold-Multimer for the prediction of protein complexes. The interpretation of these predictions has become more important than ever, but it is difficult for the non-specialist. While an evaluation of the prediction quality is provided for monomeric protein predictions by the AlphaFold Protein Structure Database, such a tool is missing for predicted complex structures. Here, we present the PAE Viewer webserver (http://www.subtiwiki.uni-goettingen.de/v4/paeViewerDemo), an online tool for the integrated visualization of predicted protein complexes using a 3D structure display combined with an interactive representation of the Predicted Aligned Error (PAE). This metric allows an estimation of the quality of the prediction. Importantly, our webserver also allows the integration of experimental cross-linking data which helps to interpret the reliability of the structure predictions. With the PAE Viewer, the user obtains a unique online tool which for the first time allows the intuitive evaluation of the PAE for protein complex structure predictions with integrated crosslinks.
Graphical Abstract
Graphical Abstract
The Predicted Aligned Error (PAE) is a metric for the reliability of protein structure predictions. The PAE Viewer webserver allows the intuitive evaluation of complex structure predictions and crosslinking data. |
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ISSN: | 0305-1048 1362-4962 |
DOI: | 10.1093/nar/gkad350 |