February 28, 2025Journal of Student ResearchOpen Access

A Machine Learning Approach for Plant-based Drug Discovery: High-Throughput Prediction of Biological Activities and Enzyme Commission Numbers from Phytochemicals and Amino Acid Sequences of Plants

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This framework predicts bioactivities and enzyme commission numbers in plant-derived natural products, suggesting improvements for drug development.

The framework predicts bioactivities with 97.62% accuracy, enhancing the efficiency of identifying plant-based drugs.
A convolutional neural network predicts enzyme commission numbers, achieving an accuracy of 81.97%.
This machine learning approach overcomes limitations of traditional screening methods for natural products.
Potential applications include drug development efficiency for various plant-derived compounds.

Kim et al. (2025) studied this question.

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This framework predicts bioactivities and enzyme commission numbers in plant-derived natural products, suggesting improvements for drug development.