Predicting Glycosyl Hydrolase Interactions and Components using Advanced Machine Learning Techniques

Vol 2, 2023 - 165772
Oral
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Abstract

We integrated QM/MM with machine learning to predict interactions
Use of Semantic segmentation to predict enzymatic components
Trained models on a dataset of glycosyl hydrolases
Achieved 85% and 95.1% accuracy for energy and component predictions, respectively

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Institutions
  • 1 Universidade Estadual de Campinas
  • 2 Universidade Estadual de Campinas / Instituto de Química / Departamento de Fisico-Química
Track
  • Machine Learning/Artificial Intelligence
Keywords
Machine Learning; Enzymatic Mechanism; QM/MM; Semantic Segmentation