Prediction of polyproline II secondary structure propensity in proteins

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Title: Prediction of polyproline II secondary structure propensity in proteins
Authors: O'Brien, KevinMooney, CatherineLopez, CyrilPollastri, GianlucaShields, Denis C.
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Date: 15-Jan-2020
Online since: 2020-12-01T15:28:51Z
Abstract: Background: The polyproline II helix (PPIIH) is an extended protein left-handed secondary structure that usually but not necessarily involves prolines. Short PPIIHs are frequently, but not exclusively, found in disordered protein regions, where they may interact with peptide-binding domains. However, no readily usable software is available to predict this state. Results: We developed PPIIPRED to predict polyproline II helix secondary structure from protein sequences, using bidirectional recurrent neural networks trained on known three-dimensional structures with dihedral angle filtering. The performance of the method was evaluated in an external validation set. In addition to proline, PPIIPRED favours amino acids whose side chains extend from the backbone (Leu, Met, Lys, Arg, Glu, Gln), as well as Ala and Val. Utility for individual residue predictions is restricted by the rarity of the PPIIH feature compared to structurally common features. Conclusion: The software, available at, is useful in large-scale studies, such as evolutionary analyses of PPIIH, or computationally reducing large datasets of candidate binding peptides for further experimental validation.
Funding Details: European Commission Horizon 2020
Science Foundation Ireland
Type of material: Journal Article
Publisher: The Royal Society
Journal: Royal Society Open Science
Volume: 7
Issue: 1
Copyright (published version): 2020 the Authors
Keywords: Proproline helixPPIIPolyproline II helicesPredictorProteinSecondary structure
DOI: 10.1098/rsos.191239
Language: en
Status of Item: Peer reviewed
ISSN: 2054-5703
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Appears in Collections:Computer Science Research Collection

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