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Molecular dynamics and binding energy analysis of Vatairea guianensis lectin: a new tool for cancer studies

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The Tn antigen is an epitope containing N-acetyl-D-galactosamine present in the extracellular matrix of some carcinoma cells in humans, and it is often used as a biomarker. Lectins are proteins capable of binding to carbohydrates and can be used as a molecular tool to recognize antigens and to differentiate cancer cells from normal cells. In this context, the present work aimed to characterize the interaction of Vatairea guianensis seed lectin with N-acetyl-D-galactosamine and the Tn antigen by molecular dynamics and molecular mechanics/Poisson–Boltzmann solvent-accessible surface area analysis. This study revealed new interacting residues not previously identified in static analysis of the three-dimensional structures of Vatairea lectins, as well as the configuration taken by the carbohydrate recognition domain, as it interacts with each ligand. During the molecular dynamics simulations, Vatairea guianensis lectin was able to bind stably to Tn antigen, which, as seen previously for other lectins, enables its use in cancer research, diagnosis, and therapy. This work further demonstrates the efficiency of bioinformatics in lectinology.

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David Martin helped with the English editing of the manuscript.


This research was supported by grants from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), and Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico (FUNCAP); Nascimento KS and Cavada BS are senior investigators of CNPq/Brazil.

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Correspondence to Benildo Sousa Cavada or Kyria Santiago Nascimento.

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Cavada, B.S., Osterne, V.J.S., Pinto-Junior, V.R. et al. Molecular dynamics and binding energy analysis of Vatairea guianensis lectin: a new tool for cancer studies. J Mol Model 26, 22 (2020). https://doi.org/10.1007/s00894-019-4281-3

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  • Tn antigen
  • Cancer
  • Vatairea guianensis
  • Lectin
  • Molecular dynamics