Polypeptide chains form open knots in many proteins. How these knotted proteins fold and finding the evolutionary advantage provided by these knots are among some of the key questions currently being studied in the protein folding field. The detection and identification of protein knots are substantial challenges. Different methods and many variations of them have been employed, but they can give different results for the same protein. In the present article, we review the various knot identification algorithms and compare their relative strengths when applied to the study of knots in proteins. We show that the statistical approach based on the uniform closure method is advantageous in comparison with other methods used to characterize protein knots.
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Conference Article|
March 21 2013
Identifying knots in proteins
Kenneth C. Millett;
Kenneth C. Millett
*Department of Mathematics, University of California Santa Barbara, 552 University Road, Santa Barbara, CA 93106, U.S.A.
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Eric J. Rawdon;
Eric J. Rawdon
†Department of Mathematics, University of St. Thomas, 2115 Summit Avenue, St. Paul, MN 55105, U.S.A.
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Andrzej Stasiak;
Andrzej Stasiak
1
‡Center for Integrative Genomics, University of Lausanne, CH-1015 Lausanne-Dorigny, Switzerland
1To whom correspondence should be addressed (email[email protected]).
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Joanna I. Sułkowska
Joanna I. Sułkowska
§Center for Theoretical Biological Physics, University of California San Diego, 9500 Gilman Drive, San Diego, CA 92037, U.S.A.
∥Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
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Publisher: Portland Press Ltd
Received:
November 15 2012
Online ISSN: 1470-8752
Print ISSN: 0300-5127
© The Authors Journal compilation © 2013 Biochemical Society
2013
Biochem Soc Trans (2013) 41 (2): 533–537.
Article history
Received:
November 15 2012
Citation
Kenneth C. Millett, Eric J. Rawdon, Andrzej Stasiak, Joanna I. Sułkowska; Identifying knots in proteins. Biochem Soc Trans 1 April 2013; 41 (2): 533–537. doi: https://doi.org/10.1042/BST20120339
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