COCONUT - Version
1
Sorokina, M., Merseburger, P., Rajan, K. et al. COCONUT online: COlleCtion
of Open Natural prodUcTs database. J Cheminform 13, 2 (2021).
https://doi.org/10.1186/s13321-020-00478-9
COCONUT data is released under the Creative Commons CC0 license, allowing for free use, modification, and distribution without any restrictions. No attribution is required when utilizing this data.
Learn how COCONUT data is currently being used
Analyse molecular structures by identifying [specific substructures like] functional groups and scaffolds, gaining insights into chemical diversity to aid in drug design, combinatorial chemistry, and molecular fingerprinting.
Synthetic feasibility and NP-likeness scores guide drug discovery by prioritizing compounds that are easier to synthesize and structurally similar to natural products, enhancing the efficiency of high-throughput screening (HTS) and deep learning models in identifying promising drug candidates.
Leverage the molecular formulas and weights of natural products to identify and characterize novel compounds, enabling the exploration of bioactive molecules with potential therapeutic applications.
