The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Rings in Drugs: Miniperspective
Abstract
We have analyzed the rings, ring systems, and frameworks in drugs listed in the FDA Orange Book to understand the frequency, timelines, molecular property space, and the application of these rings in different therapeutic areas and target classes. This analysis shows that there are only 351 ring systems and 1197 frameworks in drugs that came onto the market before 2013. Furthermore, on average six new ring systems enter drug space each year and approximately 28% of new drugs contain a new ring system. Moreover, it is very unusual for a drug to contain more than one new ring system and the majority of the most frequently used ring systems (83%) were first used in drugs developed prior to 1983. These observations give insight into the chemical novelty of drugs and potentially efficient ways to assess compound libraries and develop compounds from hit identification to lead optimization and beyond.
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Cites
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Molecular properties that influence the oral bioavailability of drug candidates
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ChEMBL: a large-scale bioactivity database for drug discovery
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Can the pharmaceutical industry reduce attrition rates?
Kola, I., & Landis, J. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1470 · Cited by 4,167
How to improve R&D productivity: the pharmaceutical industry's grand challenge
Paul, S. M., Mytelka, D. S., Dunwiddie, C. T., Persinger, C. C., Munos, B. H., Lindborg, S. R., & Schacht, A. L. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3078 · Cited by 3,566
The influence of drug-like concepts on decision-making in medicinal chemistry
Leeson, P. D., & Springthorpe, B. (2007) · Nature Reviews Drug Discovery · doi:10.1038/nrd2445 · Cited by 2,403
Can We Learn To Distinguish between “Drug-like” and “Nondrug-like” Molecules?
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Palladium-catalysed transannular C–H functionalization of alicyclic amines
Topczewski, J. J., Cabrera, P. J., Saper, N. I., & Sanford, M. S. (2016) · Nature · doi:10.1038/nature16957 · Cited by 328
eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates
Pu, L., Naderi, M., Liu, T., Wu, H.-C., Mukhopadhyay, S., & Brylinski, M. (2019) · BMC Pharmacology and Toxicology · doi:10.1186/s40360-018-0282-6 · Cited by 212
“Nitrogen-bearing heterocycles, piperidine and pi-perazine, are of central importance to medicinal chemistry [71].”
BackgroundNordquist, E. B., Zhao, M., Kumar, A., & MacKerell, A. D. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01189 · Cited by 15
(1989) · PubMed · Cited by 11
Metadata
- Authors
- Taylor, R. D., MacCoss, M., & Lawson, A. D. G.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-02-17
- Volume
- 57
- Issue
- 14
- Pages
- 5845-5859
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W2310460235
- Cited by
- 2,543
- References
- 8
- FWCI
- 80.38
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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