The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
COCONUT online: Collection of Open Natural Products database
Open accessAbstract
Natural products (NPs) are small molecules produced by living organisms with potential applications in pharmacology and other industries as many of them are bioactive. This potential raised great interest in NP research around the world and in different application fields, therefore, over the years a multiplication of generalistic and thematic NP databases has been observed. However, there is, at this moment, no online resource regrouping all known NPs in just one place, which would greatly simplify NPs research and allow computational screening and other in silico applications. In this manuscript we present the online version of the COlleCtion of Open Natural prodUcTs (COCONUT): an aggregated dataset of elucidated and predicted NPs collected from open sources and a web interface to browse, search and easily and quickly download NPs. COCONUT web is freely available at https://coconut.naturalproducts.net .
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
PubChem Substance and Compound databases
Kim, S., Thiessen, P. A., Bolton, E. E., Chen, J., Fu, G., Gindulyte, A., Han, L., He, J., He, S., Shoemaker, B. A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv951 · Cited by 5,436
ZINC 15 – Ligand Discovery for Everyone
Sterling, T., & Irwin, J. J. (2015) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5b00559 · Cited by 3,224
NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products
Kim, H. W., Wang, M., Leber, C. A., Nothias, L.-F., Reher, R., Kang, K. B., van der Hooft, J. J. J., Dorrestein, P. C., Gerwick, W. H., & Cottrell, G. W. (2021) · Journal of Natural Products · doi:10.1021/acs.jnatprod.1c00399 · Cited by 551
Cited by
NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products
Kim, H. W., Wang, M., Leber, C. A., Nothias, L.-F., Reher, R., Kang, K. B., van der Hooft, J. J. J., Dorrestein, P. C., Gerwick, W. H., & Cottrell, G. W. (2021) · Journal of Natural Products · doi:10.1021/acs.jnatprod.1c00399 · Cited by 551
Effectiveness of molecular fingerprints for exploring the chemical space of natural products
Boldini, D., Ballabio, D., Consonni, V., Todeschini, R., Grisoni, F., & Sieber, S. A. (2024) · Journal of Cheminformatics · doi:10.1186/s13321-024-00830-3 · Cited by 97
The confluence of big data and evolutionary genome mining for the discovery of natural products
Chevrette, M. G., Gavrilidou, A., Mantri, S., Selem-Mojica, N., Ziemert, N., & Barona-Gómez, F. (2021) · Natural Product Reports · doi:10.1039/d1np00013f · Cited by 66
Decoding the Foodome: Molecular Networks Connecting Diet and Health
Menichetti, G., Barabási, A.-L., & Loscalzo, J. (2024) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-062322-030557 · Cited by 32
Voronov, G., Lightheart, R., Frandsen, A., Bargh, B., Haynes, S. E., Spencer, E., Schoenhardt, K. E., Davidson, C., Schaum, A., Macherla, V. R., et al. (2022) · doi:10.1101/2022.10.09.511482 · Cited by 18
Metadata
- Authors
- Sorokina, M., Merseburger, P., Rajan, K., Yirik, M. A., & Steinbeck, C.
- Venue
- Journal of Cheminformatics
- Published
- 2021-01-10
- Volume
- 13
- Issue
- 1
- Pages
- 2-2
- ISSN
- 1758-2946 (ISSN-L)
- OpenAlex
- W3118695441
- Cited by
- 665
- References
- 3
- FWCI
- 50.61
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: COCONUT online: Collection of Open Natural Products database. https://app.cochat.ai/papers/10.1186/s13321-020-00478-9
- The paper
- Sorokina, M., Merseburger, P., Rajan, K., Yirik, M. A., & Steinbeck, C. (2021). COCONUT online: Collection of Open Natural Products database. Journal of Cheminformatics. https://doi.org/10.1186/s13321-020-00478-9
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
