View in EDS

A machine learning framework for predicting peptide inhibitors of insect voltage-gated sodium channels.

Saved in:
Bibliographic Details
Title: A machine learning framework for predicting peptide inhibitors of insect voltage-gated sodium channels.
Authors: da Silva Sousa J; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil., Palmeira LS; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil., Barbosa FS; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil., Mercado HMP; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil., Melo TS; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil., Azevedo V; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil., Góes-Neto A; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Department of Microbiology, Molecular and Computational Biology of Fungi Laboratory, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil., Xavier JS; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Computer Science Division, Technological Institute of Aeronautics, SP, São José dos Campos, 89760-000, Brazil; Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa., Andrade BS; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil. Electronic address: bandrade@uesb.edu.br.
Source: Journal of molecular graphics & modelling [J Mol Graph Model] 2026 Jul; Vol. 146, pp. 109398. Date of Electronic Publication: 2026 Apr 08.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Science, Inc Country of Publication: United States NLM ID: 9716237 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-4243 (Electronic) Linking ISSN: 10933263 NLM ISO Abbreviation: J Mol Graph Model Subsets: MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41967251
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A machine learning framework for predicting peptide inhibitors of insect voltage-gated sodium channels.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22da+Silva+Sousa+J%22">da Silva Sousa J</searchLink>; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil.<br /><searchLink fieldCode="AU" term="%22Palmeira+LS%22">Palmeira LS</searchLink>; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil.<br /><searchLink fieldCode="AU" term="%22Barbosa+FS%22">Barbosa FS</searchLink>; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil.<br /><searchLink fieldCode="AU" term="%22Mercado+HMP%22">Mercado HMP</searchLink>; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil.<br /><searchLink fieldCode="AU" term="%22Melo+TS%22">Melo TS</searchLink>; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil.<br /><searchLink fieldCode="AU" term="%22Azevedo+V%22">Azevedo V</searchLink>; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil.<br /><searchLink fieldCode="AU" term="%22Góes-Neto+A%22">Góes-Neto A</searchLink>; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Department of Microbiology, Molecular and Computational Biology of Fungi Laboratory, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil.<br /><searchLink fieldCode="AU" term="%22Xavier+JS%22">Xavier JS</searchLink>; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Computer Science Division, Technological Institute of Aeronautics, SP, São José dos Campos, 89760-000, Brazil; Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.<br /><searchLink fieldCode="AU" term="%22Andrade+BS%22">Andrade BS</searchLink>; Graduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil; Laboratory of Bioinformatics and Computational Chemistry, State University of Southwest Bahia, Jequié, BA, Brazil. Electronic address: bandrade@uesb.edu.br.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%229716237%22">Journal of molecular graphics & modelling</searchLink> [J Mol Graph Model] 2026 Jul; Vol. 146, pp. 109398. <i>Date of Electronic Publication: </i>2026 Apr 08.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Science%2C+Inc%22">Elsevier Science, Inc </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>9716237 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1873-4243 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2210933263%22">10933263 </searchLink><i>NLM ISO Abbreviation: </i>J Mol Graph Model <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41967251
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.jmgm.2026.109398
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 109398
    Titles:
      – TitleFull: A machine learning framework for predicting peptide inhibitors of insect voltage-gated sodium channels.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: da Silva Sousa J
      – PersonEntity:
          Name:
            NameFull: Palmeira LS
      – PersonEntity:
          Name:
            NameFull: Barbosa FS
      – PersonEntity:
          Name:
            NameFull: Mercado HMP
      – PersonEntity:
          Name:
            NameFull: Melo TS
      – PersonEntity:
          Name:
            NameFull: Azevedo V
      – PersonEntity:
          Name:
            NameFull: Góes-Neto A
      – PersonEntity:
          Name:
            NameFull: Xavier JS
      – PersonEntity:
          Name:
            NameFull: Andrade BS
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Text: 2026 Jul
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 1873-4243
          Numbering:
            – Type: volume
              Value: 146
          Titles:
            – TitleFull: Journal of molecular graphics & modelling
              Type: main
ResultId 1