COCONUT

COCONUT aggregates natural product data from multiple open-access sources into a consolidated dataset to support computational natural product research.

Key Features:

• Aggregated Dataset: Compiles chemical structures and associated metadata of natural products (NPs) from multiple open-access databases into a unified collection.
• Elucidated and Predicted Compounds: Includes both experimentally elucidated (validated) natural products and compounds predicted through computational methods.
• Support for Computational Screening: Provides a dataset suitable for high-throughput virtual screening and other computational analyses.

Scientific Applications:

• Computational Screening: Enables high-throughput virtual screening to identify potential bioactive natural products.
• In Silico Studies: Supports modelling of interactions between NPs and biological targets, prediction of pharmacokinetic properties, and exploration of metabolic pathways.
• Cross-Disciplinary Research: Facilitates studies spanning biochemistry, molecular biology, and medicinal chemistry by aggregating diverse NP data sources.

Methodology:

Systematic collection and aggregation of natural product records from various open-access databases, incorporating both experimentally validated and computationally predicted compound entries.