AlphaKnot 2.0: a web server for the visualization of proteins' knotting and a database of knotted AlphaFold-predicted models.


Journal

Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011

Informations de publication

Date de publication:
06 Jun 2024
Historique:
accepted: 10 05 2024
revised: 29 04 2024
received: 16 03 2024
medline: 6 6 2024
pubmed: 6 6 2024
entrez: 6 6 2024
Statut: aheadofprint

Résumé

The availability of 3D protein models is rapidly increasing with the development of structure prediction algorithms. With the expanding availability of data, new ways of analysis, especially topological analysis, of those predictions are becoming necessary. Here, we present the updated version of the AlphaKnot service that provides a straightforward way of analyzing structure topology. It was designed specifically to determine knot types of the predicted structure models, however, it can be used for all structures, including the ones solved experimentally. AlphaKnot 2.0 provides the user's ability to obtain the knowledge necessary to assess the topological correctness of the model. Both probabilistic and deterministic knot detection methods are available, together with various visualizations (including a trajectory of simplification steps to highlight the topological complexities). Moreover, the web server provides a list of proteins similar to the queried model within AlphaKnot's database and returns their knot types for direct comparison. We pre-calculated the topology of high-quality models from the AlphaFold Database (4th version) and there are now more than 680.000 knotted models available in the AlphaKnot database. AlphaKnot 2.0 is available at https://alphaknot.cent.uw.edu.pl/.

Identifiants

pubmed: 38842945
pii: 7688983
doi: 10.1093/nar/gkae443
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Narodowe Centrum Nauki
ID : UMO-2018/31/B/NZ1/04016

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.

Auteurs

Pawel Rubach (P)

Warsaw School of Economics, Al. Niepodleglosci 162, 02-554 Warsaw, Poland.

Maciej Sikora (M)

Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland.

Aleksandra I Jarmolinska (AI)

Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland.

Agata P Perlinska (AP)

Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland.

Joanna I Sulkowska (JI)

Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland.

Classifications MeSH