Taxonomic bias in AMP prediction of invertebrate peptides

Abstract Invertebrate antimicrobial peptides (AMPs) are at the forefront in the search for agents of therapeutic utility against multi-resistant microbial pathogens, and in recent years substantial advances took place in the in silico prediction of antimicrobial function of amino acid sequences. A y...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Zoltán Rádai, Johanna Kiss, Nikoletta A. Nagy
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/44a2751542f54a958d4d9824600cb3d4
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:44a2751542f54a958d4d9824600cb3d4
record_format	dspace
spelling	oai:doaj.org-article:44a2751542f54a958d4d9824600cb3d42021-12-02T17:41:12ZTaxonomic bias in AMP prediction of invertebrate peptides10.1038/s41598-021-97415-z2045-2322https://doaj.org/article/44a2751542f54a958d4d9824600cb3d42021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97415-zhttps://doaj.org/toc/2045-2322Abstract Invertebrate antimicrobial peptides (AMPs) are at the forefront in the search for agents of therapeutic utility against multi-resistant microbial pathogens, and in recent years substantial advances took place in the in silico prediction of antimicrobial function of amino acid sequences. A yet neglected aspect is taxonomic bias in the performance of these tools. Owing to differences in the prediction algorithms and used training data sets between tools, and phylogenetic differences in sequence diversity, physicochemical properties and evolved biological functions of AMPs between taxa, notable discrepancies may exist in performance between the currently available prediction tools. Here we tested if there is taxonomic bias in the prediction power in 10 tools with a total of 20 prediction algorithms in 19 invertebrate taxa, using a data set containing 1525 AMP and 3050 non-AMP sequences. We found that most of the tools exhibited considerable variation in performance between tested invertebrate groups. Based on the per-taxa performances and on the variation in performances across taxa we provide guidance in choosing the best-performing prediction tool for all assessed taxa, by listing the highest scoring tool for each of them.Zoltán RádaiJohanna KissNikoletta A. NagyNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Zoltán Rádai Johanna Kiss Nikoletta A. Nagy Taxonomic bias in AMP prediction of invertebrate peptides
description	Abstract Invertebrate antimicrobial peptides (AMPs) are at the forefront in the search for agents of therapeutic utility against multi-resistant microbial pathogens, and in recent years substantial advances took place in the in silico prediction of antimicrobial function of amino acid sequences. A yet neglected aspect is taxonomic bias in the performance of these tools. Owing to differences in the prediction algorithms and used training data sets between tools, and phylogenetic differences in sequence diversity, physicochemical properties and evolved biological functions of AMPs between taxa, notable discrepancies may exist in performance between the currently available prediction tools. Here we tested if there is taxonomic bias in the prediction power in 10 tools with a total of 20 prediction algorithms in 19 invertebrate taxa, using a data set containing 1525 AMP and 3050 non-AMP sequences. We found that most of the tools exhibited considerable variation in performance between tested invertebrate groups. Based on the per-taxa performances and on the variation in performances across taxa we provide guidance in choosing the best-performing prediction tool for all assessed taxa, by listing the highest scoring tool for each of them.
format	article
author	Zoltán Rádai Johanna Kiss Nikoletta A. Nagy
author_facet	Zoltán Rádai Johanna Kiss Nikoletta A. Nagy
author_sort	Zoltán Rádai
title	Taxonomic bias in AMP prediction of invertebrate peptides
title_short	Taxonomic bias in AMP prediction of invertebrate peptides
title_full	Taxonomic bias in AMP prediction of invertebrate peptides
title_fullStr	Taxonomic bias in AMP prediction of invertebrate peptides
title_full_unstemmed	Taxonomic bias in AMP prediction of invertebrate peptides
title_sort	taxonomic bias in amp prediction of invertebrate peptides
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/44a2751542f54a958d4d9824600cb3d4
work_keys_str_mv	AT zoltanradai taxonomicbiasinamppredictionofinvertebratepeptides AT johannakiss taxonomicbiasinamppredictionofinvertebratepeptides AT nikolettaanagy taxonomicbiasinamppredictionofinvertebratepeptides
_version_	1718379700401733632

Taxonomic bias in AMP prediction of invertebrate peptides

Ejemplares similares