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LectinOracle: A Generalizable Deep Learning Model for Lectin-Glycan Binding Prediction.

Jon Lundstrøm1,2, Emma Korhonen1,2, Frédérique Lisacek3,4,5

  • 1Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, 41390, Sweden.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|December 4, 2021
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LectinOracle, a new AI model, predicts interactions between proteins and glycans. This tool generalizes across diverse molecules, advancing glycobiology research and applications.

Keywords:
bioinformaticscarbohydratecomputational biologyglycobiologymachine learning

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Area of Science:

  • Glycobiology and computational biology.

Background:

  • Glycan-binding proteins (lectins) are vital in biological processes, from immunity to cell adhesion.
  • Studying lectin specificity is challenging due to the vast diversity of carbohydrate structures.
  • Existing methods often require piecemeal analysis, limiting generalization.

Purpose of the Study:

  • To develop a predictive model, LectinOracle, for protein-glycan interactions.
  • To overcome limitations in studying lectin specificity and enable broader applications in glycobiology.

Main Methods:

  • Developed LectinOracle, integrating transformer models for proteins and graph convolutional neural networks for glycans.
  • Trained the model on a dataset of 564,467 unique protein-glycan interactions.
  • Validated predictions using literature data and specialized glycan arrays.

Main Results:

  • LectinOracle accurately predicts known lectin specificities.
  • The model generalizes effectively to novel glycans and lectins, showing agreement with experimental data.
  • Predictions align with experimental findings on glycan arrays.

Conclusions:

  • LectinOracle provides a generalized approach to predicting protein-glycan interactions.
  • The platform can enhance lectin classification, directed evolution, and analysis of host-microbe interactions.
  • LectinOracle is poised to advance the study of lectins and their roles in (glyco)biology.