The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Alkaloids as drug leads – A predictive structural and biodiversity-based analysis
Open accessAbstract
The process of drug discovery and development particularly that of natural products, has evolved markedly over the last 30 years into increasingly formulaic approaches. As a major class of natural products initially discovered and used as early as 4000 years ago, alkaloids and the species they are derived from have been used worldwide as a source of remedies to treat a wide variety of illnesses. Yet, a tremendously wide discrepancy between their historical significance and their occurrence in modern drug development exists. Are alkaloids underrepresented in modern medicine? The physicochemical features of 27,683 alkaloids from the Dictionary of Natural Products were cross-referenced to pharmacologically significant and other metrics from various databases including the European Bioinformatics Institute's ChEMBL and Global Biodiversity Information Facility's GBIF. For the first time we show that market/developmental performance of a class of compounds is linked to its biodiversity distributions, as defined by the GBIF dataset. The potential of such a large-scale data analysis is analyzed against both prevalent rules used to guide drug discovery processes and the larger context of natural product development.
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
Natural products as sources of new drugs over the last 25 years
Newman, D. J., & Cragg, G. M. (2007) · Journal of Natural Products · doi:10.1021/np068054v · Cited by 5,517
Cited by
Natural products: A lead for drug discovery and development
Chopra, B., & Dhingra, A. K. (2021) · Phytotherapy Research · doi:10.1002/ptr.7099 · Cited by 469
Natural products for human health: an historical overview of the drug discovery approaches
Bernardini, S., Tiezzi, A., Laghezza Masci, V., & Ovidi, E. (2018) · Natural Product Research · doi:10.1080/14786419.2017.1356838 · Cited by 355
Analysis of alkaloids (indole alkaloids, isoquinoline alkaloids, tropane alkaloids)
Dey, P., Kundu, A., Kumar, A., Gupta, M., Lee, B. M., Bhakta, T., Dash, S., & Kim, H. S. (2020) · Recent Advances in Natural Products Analysis · doi:10.1016/b978-0-12-816455-6.00015-9 · Cited by 346
Metadata
- Authors
- Amirkia, V., & Heinrich, M.
- Venue
- Phytochemistry Letters
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 10
- Pages
- xlviii-liii
- ISSN
- 1874-3900 (ISSN-L)
- OpenAlex
- W2123451610
- Cited by
- 197
- References
- 1
- FWCI
- 11.05
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Alkaloids as drug leads – A predictive structural and biodiversity-based analysis. https://app.cochat.ai/papers/10.1016/j.phytol.2014.06.015
- The paper
- Amirkia, V., & Heinrich, M. (2014). Alkaloids as drug leads – A predictive structural and biodiversity-based analysis. Phytochemistry Letters. https://doi.org/10.1016/j.phytol.2014.06.015
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.