Hammock: a hidden Markov model-based peptide clustering algorithm to identify 5 protein-interaction consensus motifs in large datasets.

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00209805%3A_____%2F16%3AN0000006" target="_blank" >RIV/00209805:_____/16:N0000006 - isvavai.cz</a>

Result on the web

<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681989/" target="_blank" >http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681989/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/bioinformatics/btv522" target="_blank" >10.1093/bioinformatics/btv522</a>

Result language

angličtina

Original language name

Hammock: a hidden Markov model-based peptide clustering algorithm to identify 5 protein-interaction consensus motifs in large datasets.

Original language description

Proteins often recognize their interaction partners on the basis of short linear motifs located in disordered regions on proteins’ surface. Experimental techniques that study such motifs use short peptides to mimic the structural properties of interacting proteins. Continued development of these methods allows for large-scale screening, resulting in vast amounts of peptide sequences, potentially containing information on multiple protein-protein interactions. Processing of such datasets is a complex but essential task for large-scale studies investigating protein-protein interactions. The software tool presented in this article is able to rapidly identify multiple clusters of sequences carrying shared specificity motifs in massive datasets from various sources and generace multiple sequence alignments of identified clusters. The method was applied on a previously Publisher smaller dataset containing distinct classes of ligands for SH3 domains, as well as on a new, an order of magnitude larger dataset containing epitopes for several monoclonal antibodies. The software successfully identified clusters of sequences mimicking epitopes of antibody targets, as well as secondary clusters revealing that the antibodies accept some deviations from original epitope sequences. Another test indicates that processing of even much larger datasets is computationally feasible. Availability and implementation: Hammock is published under GNU GPL v. 3 license and is freely available as a standalone program (from http://www.recamo.cz/en/software/hammock-cluster-peptides/) or as a tool for the Galaxy toolbox (from https://toolshed.g2.bx.psu.edu/view/hammock/hammock). The source code can be downloaded from https://github.com/hammock-dev/hammock/releases.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

EB - Genetics and molecular biology

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Bioinformatics

ISSN

1367-4803

e-ISSN

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Volume of the periodical

32

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

8

Pages from-to

9-16

UT code for WoS article

000368357800002

EID of the result in the Scopus database

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