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dc.contributor.author
Aptekmann, Ariel
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dc.contributor.author
Buongiorno, J.
dc.contributor.author
Giovannelli, D.
dc.contributor.author
Glamoclija, M.
dc.contributor.author
Ferreiro, Diego
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dc.contributor.author
Bromberg, Y.
dc.date.available
2023-10-03T13:21:19Z
dc.date.issued
2022-07
dc.identifier.citation
Aptekmann, Ariel; Buongiorno, J.; Giovannelli, D.; Glamoclija, M.; Ferreiro, Diego; et al.; mebipred: identifying metal-binding potential in protein sequence; Oxford University Press; Bioinformatics (Oxford, England); 38; 14; 7-2022; 3532-3540
dc.identifier.issn
1367-4803
dc.identifier.uri
http://hdl.handle.net/11336/213940
dc.description.abstract
Motivation: metal-binding proteins have a central role in maintaining life processes. Nearly one-third of known protein structures contain metal ions that are used for a variety of needs, such as catalysis, DNA/RNA binding, protein structure stability, etc. Identifying metal-binding proteins is thus crucial for understanding the mechanisms of cellular activity. However, experimental annotation of protein metal-binding potential is severely lacking, while computational techniques are often imprecise and of limited applicability. Results: we developed a novel machine learning-based method, mebipred, for identifying metal-binding proteins from sequence-derived features. This method is over 80% accurate in recognizing proteins that bind metal ioncontaining ligands; the specific identity of 11 ubiquitously present metal ions can also be annotated. mebipred is reference-free, i.e. no sequence alignments are involved, and is thus faster than alignment-based methods; it is also more accurate than other sequence-based prediction methods. Additionally, mebipred can identify protein metalbinding capabilities from short sequence stretches, e.g. translated sequencing reads, and, thus, may be useful for the annotation of metal requirements of metagenomic samples. We performed an analysis of available microbiome data and found that ocean, hot spring sediments and soil microbiomes use a more diverse set of metals than human host-related ones. For human microbiomes, physiological conditions explain the observed metal preferences. Similarly, subtle changes in ocean sample ion concentration affect the abundance of relevant metal-binding proteins. These results highlight mebipred's utility in analyzing microbiome metal requirements.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Oxford University Press
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dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Protein metal
dc.subject
Sequence analysis
dc.subject
Mebipred
dc.subject.classification
Biología
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dc.subject.classification
Ciencias Biológicas
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
mebipred: identifying metal-binding potential in protein sequence
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-07-07T22:45:09Z
dc.journal.volume
38
dc.journal.number
14
dc.journal.pagination
3532-3540
dc.journal.pais
Reino Unido
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dc.journal.ciudad
Oxford
dc.description.fil
Fil: Aptekmann, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. Rutgers University; Estados Unidos
dc.description.fil
Fil: Buongiorno, J.. Maryville College; Estados Unidos
dc.description.fil
Fil: Giovannelli, D.. Consiglio Nazionale delle Ricerche; Italia. Università degli Studi di Napoli Federico II; Italia. Rutgers University; Estados Unidos
dc.description.fil
Fil: Glamoclija, M.. Rutgers University; Estados Unidos
dc.description.fil
Fil: Ferreiro, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina
dc.description.fil
Fil: Bromberg, Y.. Rutgers University; Estados Unidos
dc.journal.title
Bioinformatics (Oxford, England)
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/bioinformatics/article/38/14/3532/6594112
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1093/bioinformatics/btac358
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