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Matching protein surface structural patches for high-resolution blind peptide docking

Peptide docking can be perceived as a subproblem of protein–protein docking. However, due to the short length and flexible nature of peptides, many do not adopt one defined conformation prior to binding. Therefore, to tackle a peptide docking problem, not only the relative orientation, but also the...

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Autores principales: Khramushin, Alisa, Ben-Aharon, Ziv, Tsaban, Tomer, Varga, Julia K., Avraham, Orly, Schueler-Furman, Ora
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170164/
https://www.ncbi.nlm.nih.gov/pubmed/35482919
http://dx.doi.org/10.1073/pnas.2121153119
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author Khramushin, Alisa
Ben-Aharon, Ziv
Tsaban, Tomer
Varga, Julia K.
Avraham, Orly
Schueler-Furman, Ora
author_facet Khramushin, Alisa
Ben-Aharon, Ziv
Tsaban, Tomer
Varga, Julia K.
Avraham, Orly
Schueler-Furman, Ora
author_sort Khramushin, Alisa
collection PubMed
description Peptide docking can be perceived as a subproblem of protein–protein docking. However, due to the short length and flexible nature of peptides, many do not adopt one defined conformation prior to binding. Therefore, to tackle a peptide docking problem, not only the relative orientation, but also the bound conformation of the peptide needs to be modeled. Traditional peptide-centered approaches use information about peptide sequences to generate representative conformer ensembles, which can then be rigid-body docked to the receptor. Alternatively, one may look at this problem from the viewpoint of the receptor, namely, that the protein surface defines the peptide-bound conformation. Here, we present PatchMAN (Patch-Motif AligNments), a global peptide-docking approach that uses structural motifs to map the receptor surface with backbone scaffolds extracted from protein structures. On a nonredundant set of protein–peptide complexes, starting from free receptor structures, PatchMAN successfully models and identifies near-native peptide–protein complexes in 58%/84% within 2.5 Å/5 Å interface backbone RMSD, with corresponding sampling in 81%/100% of the cases, outperforming other approaches. PatchMAN leverages the observation that structural units of peptides with their binding pocket can be found not only within interfaces, but also within monomers. We show that the bound peptide conformation is sampled based on the structural context of the receptor only, without taking into account any sequence information. Beyond peptide docking, this approach opens exciting new avenues to study principles of peptide–protein association, and to the design of new peptide binders. PatchMAN is available as a server at https://furmanlab.cs.huji.ac.il/patchman/.
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spelling pubmed-91701642022-10-28 Matching protein surface structural patches for high-resolution blind peptide docking Khramushin, Alisa Ben-Aharon, Ziv Tsaban, Tomer Varga, Julia K. Avraham, Orly Schueler-Furman, Ora Proc Natl Acad Sci U S A Biological Sciences Peptide docking can be perceived as a subproblem of protein–protein docking. However, due to the short length and flexible nature of peptides, many do not adopt one defined conformation prior to binding. Therefore, to tackle a peptide docking problem, not only the relative orientation, but also the bound conformation of the peptide needs to be modeled. Traditional peptide-centered approaches use information about peptide sequences to generate representative conformer ensembles, which can then be rigid-body docked to the receptor. Alternatively, one may look at this problem from the viewpoint of the receptor, namely, that the protein surface defines the peptide-bound conformation. Here, we present PatchMAN (Patch-Motif AligNments), a global peptide-docking approach that uses structural motifs to map the receptor surface with backbone scaffolds extracted from protein structures. On a nonredundant set of protein–peptide complexes, starting from free receptor structures, PatchMAN successfully models and identifies near-native peptide–protein complexes in 58%/84% within 2.5 Å/5 Å interface backbone RMSD, with corresponding sampling in 81%/100% of the cases, outperforming other approaches. PatchMAN leverages the observation that structural units of peptides with their binding pocket can be found not only within interfaces, but also within monomers. We show that the bound peptide conformation is sampled based on the structural context of the receptor only, without taking into account any sequence information. Beyond peptide docking, this approach opens exciting new avenues to study principles of peptide–protein association, and to the design of new peptide binders. PatchMAN is available as a server at https://furmanlab.cs.huji.ac.il/patchman/. National Academy of Sciences 2022-04-28 2022-05-03 /pmc/articles/PMC9170164/ /pubmed/35482919 http://dx.doi.org/10.1073/pnas.2121153119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Khramushin, Alisa
Ben-Aharon, Ziv
Tsaban, Tomer
Varga, Julia K.
Avraham, Orly
Schueler-Furman, Ora
Matching protein surface structural patches for high-resolution blind peptide docking
title Matching protein surface structural patches for high-resolution blind peptide docking
title_full Matching protein surface structural patches for high-resolution blind peptide docking
title_fullStr Matching protein surface structural patches for high-resolution blind peptide docking
title_full_unstemmed Matching protein surface structural patches for high-resolution blind peptide docking
title_short Matching protein surface structural patches for high-resolution blind peptide docking
title_sort matching protein surface structural patches for high-resolution blind peptide docking
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170164/
https://www.ncbi.nlm.nih.gov/pubmed/35482919
http://dx.doi.org/10.1073/pnas.2121153119
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