Potential utility of docking to identify protein-peptide binding regions

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Title: Potential utility of docking to identify protein-peptide binding regions
Authors: Khan, WaqasuddinDuffy, Fergal J.Pollastri, GianlucaShields, Denis C.Mooney, Catherine
Permanent link: http://hdl.handle.net/10197/12406
Date: May-2013
Online since: 2021-08-11T11:48:41Z
Abstract: Disordered regions of proteins often bind to structured domains, mediating interactions within and between proteins. However, it is difficult to identify a priori the short regions involved in binding. We set out to determine if docking peptides to peptide binding domains would assist in these predictions. First, we investigated the docking of known short peptides to their native and non-native peptide binding domains. We then investigated the docking of overlapping peptides adjacent to the native peptide. We found only weak discrimination of docking scores between native peptide and adjacent peptides in this context with similar results for both ordered and disordered regions. Finally, we trained a bidirectional recurrent neural network using as input the peptide sequence, predicted secondary structure, Vina docking score and Pepsite score.We conclude that docking has only modest power to define the location of a peptide within a larger protein region known to contain it. However, this information can be used in training machine learning methods which may allow for the identification of peptide binding regions within a protein sequence.
Funding Details: European Commission
Science Foundation Ireland
Type of material: Technical Report
Publisher: University College Dublin. School of Computer Science and Informatics
Series/Report no.: UCD CSI Technical Reports; ucd-csi-2013-01
Copyright (published version): 2013 the Authors
Keywords: Protein-peptide interactionsProtein classificationComputational dockingRoot-mean-square deviation (RMSD)
Other versions: https://web.archive.org/web/20080226040105/http:/csiweb.ucd.ie/Research/TechnicalReports.html
Language: en
Status of Item: Not peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:CASL Research Collection
Computer Science and Informatics Technical Reports

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