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AlphaFold predicts novel human proteins with knots

The fact that proteins can have their chain formed in a knot is known for almost 30 years. However, as they are not common, only a fraction of such proteins is available in the Protein Data Bank. It was not possible to assess their importance and versatility up until now because we did not have acce...

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Autores principales: Perlinska, Agata P., Niemyska, Wanda H., Gren, Bartosz A., Bukowicki, Marek, Nowakowski, Szymon, Rubach, Pawel, Sulkowska, Joanna I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10108431/
https://www.ncbi.nlm.nih.gov/pubmed/36960558
http://dx.doi.org/10.1002/pro.4631
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author Perlinska, Agata P.
Niemyska, Wanda H.
Gren, Bartosz A.
Bukowicki, Marek
Nowakowski, Szymon
Rubach, Pawel
Sulkowska, Joanna I.
author_facet Perlinska, Agata P.
Niemyska, Wanda H.
Gren, Bartosz A.
Bukowicki, Marek
Nowakowski, Szymon
Rubach, Pawel
Sulkowska, Joanna I.
author_sort Perlinska, Agata P.
collection PubMed
description The fact that proteins can have their chain formed in a knot is known for almost 30 years. However, as they are not common, only a fraction of such proteins is available in the Protein Data Bank. It was not possible to assess their importance and versatility up until now because we did not have access to the whole proteome of an organism, let alone a human one. The arrival of efficient machine learning methods for protein structure prediction, such as AlphaFold and RoseTTaFold, changed that. We analyzed all proteins from the human proteome (over 20,000) determined with AlphaFold in search for knots and found them in less than 2% of the structures. Using a variety of methods, including homolog search, clustering, quality assessment, and visual inspection, we determined the nature of each of the knotted structures and classified it as either knotted, potentially knotted, or an artifact, and deposited all of them in a database available at: https://knotprot.cent.uw.edu.pl/alphafold. Overall, we found 51 credible knotted proteins (0.2% of human proteome). The set of potentially knotted structures includes a new complex type of a knot not reported in proteins yet. That knot type, denoted 6(3) in mathematical notation, would necessitate a more complex folding path than any knotted protein characterized to date.
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spelling pubmed-101084312023-05-01 AlphaFold predicts novel human proteins with knots Perlinska, Agata P. Niemyska, Wanda H. Gren, Bartosz A. Bukowicki, Marek Nowakowski, Szymon Rubach, Pawel Sulkowska, Joanna I. Protein Sci Full‐length Papers The fact that proteins can have their chain formed in a knot is known for almost 30 years. However, as they are not common, only a fraction of such proteins is available in the Protein Data Bank. It was not possible to assess their importance and versatility up until now because we did not have access to the whole proteome of an organism, let alone a human one. The arrival of efficient machine learning methods for protein structure prediction, such as AlphaFold and RoseTTaFold, changed that. We analyzed all proteins from the human proteome (over 20,000) determined with AlphaFold in search for knots and found them in less than 2% of the structures. Using a variety of methods, including homolog search, clustering, quality assessment, and visual inspection, we determined the nature of each of the knotted structures and classified it as either knotted, potentially knotted, or an artifact, and deposited all of them in a database available at: https://knotprot.cent.uw.edu.pl/alphafold. Overall, we found 51 credible knotted proteins (0.2% of human proteome). The set of potentially knotted structures includes a new complex type of a knot not reported in proteins yet. That knot type, denoted 6(3) in mathematical notation, would necessitate a more complex folding path than any knotted protein characterized to date. John Wiley & Sons, Inc. 2023-05-01 /pmc/articles/PMC10108431/ /pubmed/36960558 http://dx.doi.org/10.1002/pro.4631 Text en © 2023 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Full‐length Papers
Perlinska, Agata P.
Niemyska, Wanda H.
Gren, Bartosz A.
Bukowicki, Marek
Nowakowski, Szymon
Rubach, Pawel
Sulkowska, Joanna I.
AlphaFold predicts novel human proteins with knots
title AlphaFold predicts novel human proteins with knots
title_full AlphaFold predicts novel human proteins with knots
title_fullStr AlphaFold predicts novel human proteins with knots
title_full_unstemmed AlphaFold predicts novel human proteins with knots
title_short AlphaFold predicts novel human proteins with knots
title_sort alphafold predicts novel human proteins with knots
topic Full‐length Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10108431/
https://www.ncbi.nlm.nih.gov/pubmed/36960558
http://dx.doi.org/10.1002/pro.4631
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