Exhaustive search of linear information encoding protein-peptide recognition.

High-throughput in vitro methods have been extensively applied to identify linear information that encodes peptide recognition. However, these methods are limited in number of peptides, sequence variation, and length of peptides that can be explored, and often produce solutions that are not found in...

Full description

Bibliographic Details
Main Authors: Abdellali Kelil, Benjamin Dubreuil, Emmanuel D Levy, Stephen W Michnick
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-04-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC5417721?pdf=render
id doaj-f069239de1e74aea870dd917bd4b415f
record_format Article
spelling doaj-f069239de1e74aea870dd917bd4b415f2020-11-25T01:52:56ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582017-04-01134e100549910.1371/journal.pcbi.1005499Exhaustive search of linear information encoding protein-peptide recognition.Abdellali KelilBenjamin DubreuilEmmanuel D LevyStephen W MichnickHigh-throughput in vitro methods have been extensively applied to identify linear information that encodes peptide recognition. However, these methods are limited in number of peptides, sequence variation, and length of peptides that can be explored, and often produce solutions that are not found in the cell. Despite the large number of methods developed to attempt addressing these issues, the exhaustive search of linear information encoding protein-peptide recognition has been so far physically unfeasible. Here, we describe a strategy, called DALEL, for the exhaustive search of linear sequence information encoded in proteins that bind to a common partner. We applied DALEL to explore binding specificity of SH3 domains in the budding yeast Saccharomyces cerevisiae. Using only the polypeptide sequences of SH3 domain binding proteins, we succeeded in identifying the majority of known SH3 binding sites previously discovered either in vitro or in vivo. Moreover, we discovered a number of sites with both non-canonical sequences and distinct properties that may serve ancillary roles in peptide recognition. We compared DALEL to a variety of state-of-the-art algorithms in the blind identification of known binding sites of the human Grb2 SH3 domain. We also benchmarked DALEL on curated biological motifs derived from the ELM database to evaluate the effect of increasing/decreasing the enrichment of the motifs. Our strategy can be applied in conjunction with experimental data of proteins interacting with a common partner to identify binding sites among them. Yet, our strategy can also be applied to any group of proteins of interest to identify enriched linear motifs or to exhaustively explore the space of linear information encoded in a polypeptide sequence. Finally, we have developed a webserver located at http://michnick.bcm.umontreal.ca/dalel, offering user-friendly interface and providing different scenarios utilizing DALEL.http://europepmc.org/articles/PMC5417721?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Abdellali Kelil
Benjamin Dubreuil
Emmanuel D Levy
Stephen W Michnick
spellingShingle Abdellali Kelil
Benjamin Dubreuil
Emmanuel D Levy
Stephen W Michnick
Exhaustive search of linear information encoding protein-peptide recognition.
PLoS Computational Biology
author_facet Abdellali Kelil
Benjamin Dubreuil
Emmanuel D Levy
Stephen W Michnick
author_sort Abdellali Kelil
title Exhaustive search of linear information encoding protein-peptide recognition.
title_short Exhaustive search of linear information encoding protein-peptide recognition.
title_full Exhaustive search of linear information encoding protein-peptide recognition.
title_fullStr Exhaustive search of linear information encoding protein-peptide recognition.
title_full_unstemmed Exhaustive search of linear information encoding protein-peptide recognition.
title_sort exhaustive search of linear information encoding protein-peptide recognition.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2017-04-01
description High-throughput in vitro methods have been extensively applied to identify linear information that encodes peptide recognition. However, these methods are limited in number of peptides, sequence variation, and length of peptides that can be explored, and often produce solutions that are not found in the cell. Despite the large number of methods developed to attempt addressing these issues, the exhaustive search of linear information encoding protein-peptide recognition has been so far physically unfeasible. Here, we describe a strategy, called DALEL, for the exhaustive search of linear sequence information encoded in proteins that bind to a common partner. We applied DALEL to explore binding specificity of SH3 domains in the budding yeast Saccharomyces cerevisiae. Using only the polypeptide sequences of SH3 domain binding proteins, we succeeded in identifying the majority of known SH3 binding sites previously discovered either in vitro or in vivo. Moreover, we discovered a number of sites with both non-canonical sequences and distinct properties that may serve ancillary roles in peptide recognition. We compared DALEL to a variety of state-of-the-art algorithms in the blind identification of known binding sites of the human Grb2 SH3 domain. We also benchmarked DALEL on curated biological motifs derived from the ELM database to evaluate the effect of increasing/decreasing the enrichment of the motifs. Our strategy can be applied in conjunction with experimental data of proteins interacting with a common partner to identify binding sites among them. Yet, our strategy can also be applied to any group of proteins of interest to identify enriched linear motifs or to exhaustively explore the space of linear information encoded in a polypeptide sequence. Finally, we have developed a webserver located at http://michnick.bcm.umontreal.ca/dalel, offering user-friendly interface and providing different scenarios utilizing DALEL.
url http://europepmc.org/articles/PMC5417721?pdf=render
work_keys_str_mv AT abdellalikelil exhaustivesearchoflinearinformationencodingproteinpeptiderecognition
AT benjamindubreuil exhaustivesearchoflinearinformationencodingproteinpeptiderecognition
AT emmanueldlevy exhaustivesearchoflinearinformationencodingproteinpeptiderecognition
AT stephenwmichnick exhaustivesearchoflinearinformationencodingproteinpeptiderecognition
_version_ 1724991856371040256