Cargando…
Proteins comparison through probabilistic optimal structure local alignment
Multiple local structure comparison helps to identify common structural motifs or conserved binding sites in 3D structures in distantly related proteins. Since there is no best way to compare structures and evaluate the alignment, a wide variety of techniques and different similarity scoring schemes...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4151033/ https://www.ncbi.nlm.nih.gov/pubmed/25228906 http://dx.doi.org/10.3389/fgene.2014.00302 |
_version_ | 1782332989826400256 |
---|---|
author | Micale, Giovanni Pulvirenti, Alfredo Giugno, Rosalba Ferro, Alfredo |
author_facet | Micale, Giovanni Pulvirenti, Alfredo Giugno, Rosalba Ferro, Alfredo |
author_sort | Micale, Giovanni |
collection | PubMed |
description | Multiple local structure comparison helps to identify common structural motifs or conserved binding sites in 3D structures in distantly related proteins. Since there is no best way to compare structures and evaluate the alignment, a wide variety of techniques and different similarity scoring schemes have been proposed. Existing algorithms usually compute the best superposition of two structures or attempt to solve it as an optimization problem in a simpler setting (e.g., considering contact maps or distance matrices). Here, we present PROPOSAL (PROteins comparison through Probabilistic Optimal Structure local ALignment), a stochastic algorithm based on iterative sampling for multiple local alignment of protein structures. Our method can efficiently find conserved motifs across a set of protein structures. Only the distances between all pairs of residues in the structures are computed. To show the accuracy and the effectiveness of PROPOSAL we tested it on a few families of protein structures. We also compared PROPOSAL with two state-of-the-art tools for pairwise local alignment on a dataset of manually annotated motifs. PROPOSAL is available as a Java 2D standalone application or a command line program at http://ferrolab.dmi.unict.it/proposal/proposal.html. |
format | Online Article Text |
id | pubmed-4151033 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-41510332014-09-16 Proteins comparison through probabilistic optimal structure local alignment Micale, Giovanni Pulvirenti, Alfredo Giugno, Rosalba Ferro, Alfredo Front Genet Genetics Multiple local structure comparison helps to identify common structural motifs or conserved binding sites in 3D structures in distantly related proteins. Since there is no best way to compare structures and evaluate the alignment, a wide variety of techniques and different similarity scoring schemes have been proposed. Existing algorithms usually compute the best superposition of two structures or attempt to solve it as an optimization problem in a simpler setting (e.g., considering contact maps or distance matrices). Here, we present PROPOSAL (PROteins comparison through Probabilistic Optimal Structure local ALignment), a stochastic algorithm based on iterative sampling for multiple local alignment of protein structures. Our method can efficiently find conserved motifs across a set of protein structures. Only the distances between all pairs of residues in the structures are computed. To show the accuracy and the effectiveness of PROPOSAL we tested it on a few families of protein structures. We also compared PROPOSAL with two state-of-the-art tools for pairwise local alignment on a dataset of manually annotated motifs. PROPOSAL is available as a Java 2D standalone application or a command line program at http://ferrolab.dmi.unict.it/proposal/proposal.html. Frontiers Media S.A. 2014-09-02 /pmc/articles/PMC4151033/ /pubmed/25228906 http://dx.doi.org/10.3389/fgene.2014.00302 Text en Copyright © 2014 Micale, Pulvirenti, Giugno and Ferro. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Micale, Giovanni Pulvirenti, Alfredo Giugno, Rosalba Ferro, Alfredo Proteins comparison through probabilistic optimal structure local alignment |
title | Proteins comparison through probabilistic optimal structure local alignment |
title_full | Proteins comparison through probabilistic optimal structure local alignment |
title_fullStr | Proteins comparison through probabilistic optimal structure local alignment |
title_full_unstemmed | Proteins comparison through probabilistic optimal structure local alignment |
title_short | Proteins comparison through probabilistic optimal structure local alignment |
title_sort | proteins comparison through probabilistic optimal structure local alignment |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4151033/ https://www.ncbi.nlm.nih.gov/pubmed/25228906 http://dx.doi.org/10.3389/fgene.2014.00302 |
work_keys_str_mv | AT micalegiovanni proteinscomparisonthroughprobabilisticoptimalstructurelocalalignment AT pulvirentialfredo proteinscomparisonthroughprobabilisticoptimalstructurelocalalignment AT giugnorosalba proteinscomparisonthroughprobabilisticoptimalstructurelocalalignment AT ferroalfredo proteinscomparisonthroughprobabilisticoptimalstructurelocalalignment |