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The Expansin Engineering Database: a navigation and classification tool for expansins and homologues
  • +1
  • Caroline Lohoff,
  • Patrick Buchholz,
  • Marilize Le Roes - Hill,
  • Juergen Pleiss
Caroline Lohoff
University of Stuttgart
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Patrick Buchholz
University of Stuttgart
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Marilize Le Roes - Hill
Cape Peninsula University of Technology
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Juergen Pleiss
University of Stuttgart
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Peer review status:UNDER REVIEW

03 Apr 2020Submitted to PROTEINS: Structure, Function, and Bioinformatics
06 Apr 2020Submission Checks Completed
06 Apr 2020Assigned to Editor
23 Apr 2020Reviewer(s) Assigned
06 Jun 2020Review(s) Completed, Editorial Evaluation Pending
07 Jun 2020Editorial Decision: Revise Minor
15 Jun 20201st Revision Received
17 Jun 2020Submission Checks Completed
17 Jun 2020Assigned to Editor
16 Jul 2020Reviewer(s) Assigned

Abstract

Expansins have the remarkable ability to loosen plant cell walls and cellulose material without showing catalytic activity and therefore have potential applications in biomass degradation. To support the study of sequence-structure-function relationships and the search for novel expansins, the Expansin Engineering Database (ExED, https://exed.biocatnet.de) collected sequence and structure data on expansins from Bacteria, Fungi, and Viridiplantae, and expansin-like homologues such as carbohydrate binding modules, glycoside hydrolases, loosenins, swollenins, cerato-platanins, and EXPNs. Based on global sequence alignment and protein sequence network analysis, the sequences are highly diverse. However, many similarities were found between the expansin domains. Newly created profile hidden Markov models of the two expansin domains enable standard numbering schemes, comprehensive conservation analyses, and genome annotation. Conserved key amino acids in the expansin domains were identified, a refined classification of expansins and carbohydrate binding modules was proposed, and new sequence motifs facilitate the search of novel candidate genes and the engineering of expansins.