SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1093/nar/gkac029 http://hdl.handle.net/11449/240818 |
Resumo: | Proteins isolated from natural sources can be composed of a mixture of isoforms with similar physicochemical properties that coexist in the final steps of purification. Yet, even where unverified, the assumed sequence is enforced throughout the structural studies. Herein, we propose a novel perspective to address the usually neglected sequence heterogeneity of natural products by integrating biophysical, genetic and structural data in our program SEQUENCE SLIDER. The aim is to assess the evidence supporting chemical composition in structure determination. Locally, we interrogate the experimental map to establish which side chains are supported by the structural data, and the genetic information relating sequence conservation is integrated into this statistic. Hence, we build a constrained peptide database, containing most probable sequences to interpret mass spectrometry data (MS). In parallel, we perform MS de novo sequencing with genomic-based algorithms to detect point mutations. We calibrated SLIDER with Gallus gallus lysozyme, whose sequence is unequivocally established and numerous natural isoforms are reported. We used SLIDER to characterize a metalloproteinase and a phospholipase A2-like protein from the venom of Bothrops moojeni and a crotoxin from Crotalus durissus collilineatus. This integrated approach offers a more realistic structural descriptor to characterize macromolecules isolated from natural sources. |
id |
UNSP_9997a0536dea3c687cdbdc960559635e |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/240818 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sourcesProteins isolated from natural sources can be composed of a mixture of isoforms with similar physicochemical properties that coexist in the final steps of purification. Yet, even where unverified, the assumed sequence is enforced throughout the structural studies. Herein, we propose a novel perspective to address the usually neglected sequence heterogeneity of natural products by integrating biophysical, genetic and structural data in our program SEQUENCE SLIDER. The aim is to assess the evidence supporting chemical composition in structure determination. Locally, we interrogate the experimental map to establish which side chains are supported by the structural data, and the genetic information relating sequence conservation is integrated into this statistic. Hence, we build a constrained peptide database, containing most probable sequences to interpret mass spectrometry data (MS). In parallel, we perform MS de novo sequencing with genomic-based algorithms to detect point mutations. We calibrated SLIDER with Gallus gallus lysozyme, whose sequence is unequivocally established and numerous natural isoforms are reported. We used SLIDER to characterize a metalloproteinase and a phospholipase A2-like protein from the venom of Bothrops moojeni and a crotoxin from Crotalus durissus collilineatus. This integrated approach offers a more realistic structural descriptor to characterize macromolecules isolated from natural sources.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Ministerio de Ciencia e InnovaciónDepartament of Biophysics and Pharmacology Biosciences Institute São Paulo State University (UNESP)Crystallographic Methods Institute of Molecular Biology of Barcelona (IBMB-CSIC)Biochemistry and Biophysics Laboratory, Butantan Institute, São Paulo, São Paulo 05503-900, BrazilGraduate Program in Tropical Diseases Botucatu Medical School (FMB) São Paulo State University (UNESP)Biotechnology Institute (IBTEC) São Paulo State University (UNESP)ICREA, Pg. Lluís Companys 23Departament of Biophysics and Pharmacology Biosciences Institute São Paulo State University (UNESP)Graduate Program in Tropical Diseases Botucatu Medical School (FMB) São Paulo State University (UNESP)Biotechnology Institute (IBTEC) São Paulo State University (UNESP)FAPESP: 2015/17286-0FAPESP: 2016/24191-8CNPq: 301974/2019-5Ministerio de Ciencia e Innovación: PGC2018-101370-BI00 AEI/FEDER/UEUniversidade Estadual Paulista (UNESP)Institute of Molecular Biology of Barcelona (IBMB-CSIC)ICREABorges, Rafael J. [UNESP]Salvador, Guilherme H M [UNESP]Pimenta, Daniel C.Santos, Lucilene D. dos [UNESP]Fontes, Marcos R M [UNESP]Usón, Isabel2023-03-01T20:34:01Z2023-03-01T20:34:01Z2022-05-20info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlee50http://dx.doi.org/10.1093/nar/gkac029Nucleic acids research, v. 50, n. 9, p. e50-, 2022.1362-4962http://hdl.handle.net/11449/24081810.1093/nar/gkac0292-s2.0-85125647931Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengNucleic acids researchinfo:eu-repo/semantics/openAccess2023-03-01T20:34:01Zoai:repositorio.unesp.br:11449/240818Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-03-01T20:34:01Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources |
title |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources |
spellingShingle |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources Borges, Rafael J. [UNESP] |
title_short |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources |
title_full |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources |
title_fullStr |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources |
title_full_unstemmed |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources |
title_sort |
SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources |
author |
Borges, Rafael J. [UNESP] |
author_facet |
Borges, Rafael J. [UNESP] Salvador, Guilherme H M [UNESP] Pimenta, Daniel C. Santos, Lucilene D. dos [UNESP] Fontes, Marcos R M [UNESP] Usón, Isabel |
author_role |
author |
author2 |
Salvador, Guilherme H M [UNESP] Pimenta, Daniel C. Santos, Lucilene D. dos [UNESP] Fontes, Marcos R M [UNESP] Usón, Isabel |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Institute of Molecular Biology of Barcelona (IBMB-CSIC) ICREA |
dc.contributor.author.fl_str_mv |
Borges, Rafael J. [UNESP] Salvador, Guilherme H M [UNESP] Pimenta, Daniel C. Santos, Lucilene D. dos [UNESP] Fontes, Marcos R M [UNESP] Usón, Isabel |
description |
Proteins isolated from natural sources can be composed of a mixture of isoforms with similar physicochemical properties that coexist in the final steps of purification. Yet, even where unverified, the assumed sequence is enforced throughout the structural studies. Herein, we propose a novel perspective to address the usually neglected sequence heterogeneity of natural products by integrating biophysical, genetic and structural data in our program SEQUENCE SLIDER. The aim is to assess the evidence supporting chemical composition in structure determination. Locally, we interrogate the experimental map to establish which side chains are supported by the structural data, and the genetic information relating sequence conservation is integrated into this statistic. Hence, we build a constrained peptide database, containing most probable sequences to interpret mass spectrometry data (MS). In parallel, we perform MS de novo sequencing with genomic-based algorithms to detect point mutations. We calibrated SLIDER with Gallus gallus lysozyme, whose sequence is unequivocally established and numerous natural isoforms are reported. We used SLIDER to characterize a metalloproteinase and a phospholipase A2-like protein from the venom of Bothrops moojeni and a crotoxin from Crotalus durissus collilineatus. This integrated approach offers a more realistic structural descriptor to characterize macromolecules isolated from natural sources. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-05-20 2023-03-01T20:34:01Z 2023-03-01T20:34:01Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1093/nar/gkac029 Nucleic acids research, v. 50, n. 9, p. e50-, 2022. 1362-4962 http://hdl.handle.net/11449/240818 10.1093/nar/gkac029 2-s2.0-85125647931 |
url |
http://dx.doi.org/10.1093/nar/gkac029 http://hdl.handle.net/11449/240818 |
identifier_str_mv |
Nucleic acids research, v. 50, n. 9, p. e50-, 2022. 1362-4962 10.1093/nar/gkac029 2-s2.0-85125647931 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Nucleic acids research |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
e50 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1799965180341256192 |