The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Interactive SAR Studies: Rational Discovery of Super-Potent and Highly Selective Dopamine D3 Receptor Antagonists and Partial Agonists
Open accessAbstract
Starting from dopamine receptor ligand BP897, an interactive drug discovery process leading to heterocyclic bioisosteres is demonstrated. The four step strategy involved a careful optimization of geometric and electronic properties by systematic modification of the attachment points and heteroatoms, respectively. Efficacy tuning by modification of the phenyl substituents led to both D3 partial agonists and full antagonists. The benzothiophenes 3c (FAUC346) and 3d (FAUC365) revealed outstanding D3 affinity and subtype selectivity.
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Cites
Modulation of intracellular cyclic AMP levels by different human dopamine D4 receptor variants
Asghari, V., Sanyal, S., Buchwaldt, S., Paterson, A., Jovanovic, V., & Van Tol, H. H. M. (1995) · Journal of Neurochemistry · doi:10.1046/j.1471-4159.1995.65031157.x · Cited by 858
Cited by
Zhang, A., Neumeyer, J. L., & Baldessarini, R. J. (2007) · Chemical Reviews · doi:10.1021/cr050263h · Cited by 428
Metadata
- Authors
- Bettinetti, L., Schlotter, K., Hübner, H., & Gmeiner, P.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2002-09-06
- Volume
- 45
- Issue
- 21
- Pages
- 4594-4597
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W1980740634
- Cited by
- 194
- References
- 1
- FWCI
- 12.90
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Interactive SAR Studies: Rational Discovery of Super-Potent and Highly Selective Dopamine D3 Receptor Antagonists and Partial Agonists. https://app.cochat.ai/papers/10.1021/jm025558r
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- Bettinetti, L., Schlotter, K., Hübner, H., & Gmeiner, P. (2002). Interactive SAR Studies: Rational Discovery of Super-Potent and Highly Selective Dopamine D3 Receptor Antagonists and Partial Agonists. Journal of Medicinal Chemistry. https://doi.org/10.1021/jm025558r
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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.
