Mechanical strength of 17,134 model proteins and cysteine slipknots.

A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17,134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies...

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Main Authors: Mateusz Sikora, Joanna I Sułkowska, Marek Cieplak
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2009-10-01
Series:PLoS Computational Biology
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19876372/pdf/?tool=EBI
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spelling doaj-18c945ee5b49417f864af3a476fa83cc2021-04-21T15:08:33ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582009-10-01510e100054710.1371/journal.pcbi.1000547Mechanical strength of 17,134 model proteins and cysteine slipknots.Mateusz SikoraJoanna I SułkowskaMarek CieplakA new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17,134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cysteine slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19876372/pdf/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Mateusz Sikora
Joanna I Sułkowska
Marek Cieplak
spellingShingle Mateusz Sikora
Joanna I Sułkowska
Marek Cieplak
Mechanical strength of 17,134 model proteins and cysteine slipknots.
PLoS Computational Biology
author_facet Mateusz Sikora
Joanna I Sułkowska
Marek Cieplak
author_sort Mateusz Sikora
title Mechanical strength of 17,134 model proteins and cysteine slipknots.
title_short Mechanical strength of 17,134 model proteins and cysteine slipknots.
title_full Mechanical strength of 17,134 model proteins and cysteine slipknots.
title_fullStr Mechanical strength of 17,134 model proteins and cysteine slipknots.
title_full_unstemmed Mechanical strength of 17,134 model proteins and cysteine slipknots.
title_sort mechanical strength of 17,134 model proteins and cysteine slipknots.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2009-10-01
description A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17,134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cysteine slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19876372/pdf/?tool=EBI
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