Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.

The binding of short disordered peptide stretches to globular protein domains is important for a wide range of cellular processes, including signal transduction, protein transport, and immune response. The often promiscuous nature of these interactions and the conformational flexibility of the pepti...

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Main Authors: Arnab Bhattacherjee, Stefan Wallin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-10-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC3812049?pdf=render
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spelling doaj-aa0d62c2ef304bbdb0aef45a10f38ede2020-11-25T01:11:55ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582013-10-01910e100327710.1371/journal.pcbi.1003277Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.Arnab BhattacherjeeStefan WallinThe binding of short disordered peptide stretches to globular protein domains is important for a wide range of cellular processes, including signal transduction, protein transport, and immune response. The often promiscuous nature of these interactions and the conformational flexibility of the peptide chain, sometimes even when bound, make the binding specificity of this type of protein interaction a challenge to understand. Here we develop and test a Monte Carlo-based procedure for calculating protein-peptide binding thermodynamics for many sequences in a single run. The method explores both peptide sequence and conformational space simultaneously by simulating a joint probability distribution which, in particular, makes searching through peptide sequence space computationally efficient. To test our method, we apply it to 3 different peptide-binding protein domains and test its ability to capture the experimentally determined specificity profiles. Insight into the molecular underpinnings of the observed specificities is obtained by analyzing the peptide conformational ensembles of a large number of binding-competent sequences. We also explore the possibility of using our method to discover new peptide-binding pockets on protein structures.http://europepmc.org/articles/PMC3812049?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Arnab Bhattacherjee
Stefan Wallin
spellingShingle Arnab Bhattacherjee
Stefan Wallin
Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.
PLoS Computational Biology
author_facet Arnab Bhattacherjee
Stefan Wallin
author_sort Arnab Bhattacherjee
title Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.
title_short Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.
title_full Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.
title_fullStr Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.
title_full_unstemmed Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.
title_sort exploring protein-peptide binding specificity through computational peptide screening.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2013-10-01
description The binding of short disordered peptide stretches to globular protein domains is important for a wide range of cellular processes, including signal transduction, protein transport, and immune response. The often promiscuous nature of these interactions and the conformational flexibility of the peptide chain, sometimes even when bound, make the binding specificity of this type of protein interaction a challenge to understand. Here we develop and test a Monte Carlo-based procedure for calculating protein-peptide binding thermodynamics for many sequences in a single run. The method explores both peptide sequence and conformational space simultaneously by simulating a joint probability distribution which, in particular, makes searching through peptide sequence space computationally efficient. To test our method, we apply it to 3 different peptide-binding protein domains and test its ability to capture the experimentally determined specificity profiles. Insight into the molecular underpinnings of the observed specificities is obtained by analyzing the peptide conformational ensembles of a large number of binding-competent sequences. We also explore the possibility of using our method to discover new peptide-binding pockets on protein structures.
url http://europepmc.org/articles/PMC3812049?pdf=render
work_keys_str_mv AT arnabbhattacherjee exploringproteinpeptidebindingspecificitythroughcomputationalpeptidescreening
AT stefanwallin exploringproteinpeptidebindingspecificitythroughcomputationalpeptidescreening
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