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DAMA: a method for computing multiple alignments of protein structures using local structure descriptors

MOTIVATION: The well-known fact that protein structures are more conserved than their sequences forms the basis of several areas of computational structural biology. Methods based on the structure analysis provide more complete information on residue conservation in evolutionary processes. This is c...

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Autores principales: Daniluk, Paweł, Oleniecki, Tymoteusz, Lesyng, Bogdan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8696102/
https://www.ncbi.nlm.nih.gov/pubmed/34396393
http://dx.doi.org/10.1093/bioinformatics/btab571
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author Daniluk, Paweł
Oleniecki, Tymoteusz
Lesyng, Bogdan
author_facet Daniluk, Paweł
Oleniecki, Tymoteusz
Lesyng, Bogdan
author_sort Daniluk, Paweł
collection PubMed
description MOTIVATION: The well-known fact that protein structures are more conserved than their sequences forms the basis of several areas of computational structural biology. Methods based on the structure analysis provide more complete information on residue conservation in evolutionary processes. This is crucial for the determination of evolutionary relationships between proteins and for the identification of recurrent structural patterns present in biomolecules involved in similar functions. However, algorithmic structural alignment is much more difficult than multiple sequence alignment. This study is devoted to the development and applications of DAMA—a novel effective environment capable to compute and analyze multiple structure alignments. RESULTS: DAMA is based on local structural similarities, using local 3D structure descriptors and thus accounts for nearest-neighbor molecular environments of aligned residues. It is constrained neither by protein topology nor by its global structure. DAMA is an extension of our previous study (DEDAL) which demonstrated the applicability of local descriptors to pairwise alignment problems. Since the multiple alignment problem is NP-complete, an effective heuristic approach has been developed without imposing any artificial constraints. The alignment algorithm searches for the largest, consistent ensemble of similar descriptors. The new method is capable to capture most of the biologically significant similarities present in canonical test sets and is discriminatory enough to prevent the emergence of larger, but meaningless, solutions. Tests performed on the test sets, including protein kinases, demonstrate DAMA’s capability of identifying equivalent residues, which should be very useful in discovering the biological nature of proteins similarity. Performance profiles show the advantage of DAMA over other methods, in particular when using a strict similarity measure Q(C), which is the ratio of correctly aligned columns, and when applying the methods to more difficult cases. AVAILABILITY AND IMPLEMENTATION: DAMA is available online at http://dworkowa.imdik.pan.pl/EP/DAMA. Linux binaries of the software are available upon request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-86961022022-01-04 DAMA: a method for computing multiple alignments of protein structures using local structure descriptors Daniluk, Paweł Oleniecki, Tymoteusz Lesyng, Bogdan Bioinformatics Original Papers MOTIVATION: The well-known fact that protein structures are more conserved than their sequences forms the basis of several areas of computational structural biology. Methods based on the structure analysis provide more complete information on residue conservation in evolutionary processes. This is crucial for the determination of evolutionary relationships between proteins and for the identification of recurrent structural patterns present in biomolecules involved in similar functions. However, algorithmic structural alignment is much more difficult than multiple sequence alignment. This study is devoted to the development and applications of DAMA—a novel effective environment capable to compute and analyze multiple structure alignments. RESULTS: DAMA is based on local structural similarities, using local 3D structure descriptors and thus accounts for nearest-neighbor molecular environments of aligned residues. It is constrained neither by protein topology nor by its global structure. DAMA is an extension of our previous study (DEDAL) which demonstrated the applicability of local descriptors to pairwise alignment problems. Since the multiple alignment problem is NP-complete, an effective heuristic approach has been developed without imposing any artificial constraints. The alignment algorithm searches for the largest, consistent ensemble of similar descriptors. The new method is capable to capture most of the biologically significant similarities present in canonical test sets and is discriminatory enough to prevent the emergence of larger, but meaningless, solutions. Tests performed on the test sets, including protein kinases, demonstrate DAMA’s capability of identifying equivalent residues, which should be very useful in discovering the biological nature of proteins similarity. Performance profiles show the advantage of DAMA over other methods, in particular when using a strict similarity measure Q(C), which is the ratio of correctly aligned columns, and when applying the methods to more difficult cases. AVAILABILITY AND IMPLEMENTATION: DAMA is available online at http://dworkowa.imdik.pan.pl/EP/DAMA. Linux binaries of the software are available upon request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-08-16 /pmc/articles/PMC8696102/ /pubmed/34396393 http://dx.doi.org/10.1093/bioinformatics/btab571 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Daniluk, Paweł
Oleniecki, Tymoteusz
Lesyng, Bogdan
DAMA: a method for computing multiple alignments of protein structures using local structure descriptors
title DAMA: a method for computing multiple alignments of protein structures using local structure descriptors
title_full DAMA: a method for computing multiple alignments of protein structures using local structure descriptors
title_fullStr DAMA: a method for computing multiple alignments of protein structures using local structure descriptors
title_full_unstemmed DAMA: a method for computing multiple alignments of protein structures using local structure descriptors
title_short DAMA: a method for computing multiple alignments of protein structures using local structure descriptors
title_sort dama: a method for computing multiple alignments of protein structures using local structure descriptors
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8696102/
https://www.ncbi.nlm.nih.gov/pubmed/34396393
http://dx.doi.org/10.1093/bioinformatics/btab571
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