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Glycan Binding Profiling of Jacalin-Related Lectins from the Pteria Penguin Pearl Shell.

Tomohisa OgawaRie SatoTakako NaganumaKayeu LiuAgness Ethel LakudzalaKoji MuramotoMakoto OsadaKyosuke YoshimiKeiko HiemoriJun HirabayashiHiroaki Tateno
Published in: International journal of molecular sciences (2019)
We determined the primary structures of jacalin-related lectins termed PPL3s (PPL3A, 3B, and 3C, which are dimers consisting of sequence variants α + α, α + β, β + β, respectively) and PPL4, which is heterodimer consisting of α + β subunits, isolated from mantle secretory fluid of Pteria penguin (Mabe) pearl shell. Their carbohydrate-binding properties were analyzed, in addition to that of PPL2A, which was previously reported as a matrix protein. PPL3s and PPL4 shared only 35-50% homology to PPL2A, respectively; they exhibited significantly different carbohydrate-binding specificities based on the multiple glycan binding profiling data sets from frontal affinity chromatography analysis. The carbohydrate-binding specificity of PPL3s was similar to that of PPL2A, except only for Man3Fuc1Xyl1GlcNAc2 oligosaccharide, while PPL4 showed different carbohydrate-binding specificity compared with PPL2A and PPL3s. PPL2A and PPL3s mainly recognize agalactosylated- and galactosylated-type glycans. On the other hand, PPL4 binds to high-mannose-and hybrid-type N-linked glycans but not agalactosylated- and galactosylated-type glycans.
Keyphrases
  • binding protein
  • dna binding
  • mass spectrometry
  • single cell
  • machine learning
  • working memory
  • transcription factor
  • deep learning
  • artificial intelligence
  • electronic health record
  • ms ms
  • high speed