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Identification of Key Residues in Proteins Through Centrality Analysis and Flexibility Prediction with RINspector.
Brysbaert, Guillaume; Mauri, Théo; de Ruyck, Jérôme; Lensink, Marc F.
Affiliation
  • Brysbaert G; University of Lille, CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, F-59000 Lille, France.
  • Mauri T; University of Lille, CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, F-59000 Lille, France.
  • de Ruyck J; University of Lille, CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, F-59000 Lille, France.
  • Lensink MF; University of Lille, CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, F-59000 Lille, France.
Curr Protoc Bioinformatics ; 65(1): e66, 2019 03.
Article in En | MEDLINE | ID: mdl-30489695
ABSTRACT
Protein structures inherently contain information that can be used to decipher their functions, but the exploitation of this knowledge is not trivial. We recently developed an app for the Cytoscape network visualization and analysis program, called RINspector, the goal of which is to integrate two different approaches that identify key residues in a protein structure or complex. The first approach consists of calculating centralities on a residue interaction network (RIN) generated from the three-dimensional structure; the second consists of predicting backbone flexibility and needs only the primary sequence. The identified residues are highly correlated with functional relevance and constitute a good set of targets for mutagenesis experiments. Here we present a protocol that details in a step-by-step fashion how to create a RIN from a structure and then calculate centralities and predict flexibilities. We also discuss how to understand and use the results of the analyses. © 2018 by John Wiley & Sons, Inc.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Proteins / Computational Biology Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Curr Protoc Bioinformatics Year: 2019 Document type: Article Affiliation country: France

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Proteins / Computational Biology Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Curr Protoc Bioinformatics Year: 2019 Document type: Article Affiliation country: France