READRetro

READRetro integrates a machine learning model for predicting plant natural product biosynthesis through retrosynthesis prediction.

Key Features:

• Retrosynthesis prediction: The READRetro machine learning model predicts biosynthetic pathways for plant natural products to facilitate retrosynthetic pathway design.
• High predictive accuracy: The platform demonstrates high predictive accuracy for natural product retrosynthesis.
• Computational efficiency: The platform offers computational efficiency in generating predictions.
• Organized results: The platform provides well-organized results to facilitate natural product retrosynthetic pathway design.

Scientific Applications:

• Natural product biosynthesis prediction: Predicts biosynthetic pathways for plant natural products to support metabolic engineering and biosynthesis approaches.
• Pharmaceutical research and drug discovery: Accelerates natural product discovery by identifying ideal pathways for mass production of bioactive molecules.
• Retrosynthetic pathway design: Facilitates the design of retrosynthetic pathways for natural products to enable large-scale production.

Methodology:

The READRetro machine learning model is used for retrosynthesis prediction.