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In silico identification of glycosylphosphatidylinositol-anchored proteins in Paracoccidioides spp.

Relber Aguiar GonçalesAyda Lm SalamancaLuiz Rb JúniorKleber Sf E SilvaElton Jr de VasconcelosThaila F Dos ReisRicardo C CastroPatrícia de C RuyBárbara RomagnoliJerônimo RuizMaristela PereiraCélia Maria de Almeida SoaresPaulo Sr Coelho
Published in: Future microbiology (2021)
Aim: To predict glycosylphosphatidylinositol (GPI)-anchored proteins in the genome of Paracoccidioides brasiliensis and Paracoccidioides lutzii. Materials & methods: Five different bioinformatics tools were used for predicting GPI-anchored proteins; we considered as GPI-anchored proteins those detected by at least two in silico analysis methods. We also performed the proteomic analysis of P. brasiliensis cell wall by mass spectrometry. Results: Hundred GPI-anchored proteins were predicted in P. brasiliensis and P. lutzii genomes. A series of 57 proteins were classified in functional categories and 43 conserved proteins were reported with unknown functions. Four proteins identified by in silico analyses were also identified in the cell wall proteome. Conclusion: The data obtained in this study are important resources for future research of GPI-anchored proteins in Paracoccidioides spp. to identify targets for new diagnostic tools, drugs and immunological tests.
Keyphrases
  • cell wall
  • mass spectrometry
  • molecular docking
  • gene expression
  • dna methylation
  • machine learning
  • transcription factor
  • genome wide
  • artificial intelligence
  • drug induced