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Cited by 408

The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.

The Necessary Nitrogen Atom: A Versatile High-Impact Design Element for Multiparameter Optimization

Open access
Pennington, Lewis D., Moustakas, Demetri T.·2017·Journal of Medicinal Chemistry

Abstract

There is a continued desire in biomedical research to reduce the number and duration of design cycles required to optimize lead compounds into high-quality chemical probes or safe and efficacious drug candidates. The insightful application of impactful molecular design elements is one approach toward achieving this goal. The replacement of a CH group with a N atom in aromatic and heteroaromatic ring systems can have many important effects on molecular and physicochemical properties and intra- and intermolecular interactions that can translate to improved pharmacological profiles. In this Perspective, the "necessary nitrogen atom" is shown to be a versatile high-impact design element for multiparameter optimization, wherein ≥10-, 100-, or 1000-fold improvement in a variety of key pharmacological parameters can be realized.

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Crossref · 10.1021/acs.jmedchem.6b01807

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Metadata

Authors
Pennington, L. D., & Moustakas, D. T.
Venue
Journal of Medicinal Chemistry
Published
2017-02-08
Volume
60
Issue
9
Pages
3552-3579
ISSN
  • 0022-2623 (ISSN-L)
  • 1520-4804
OpenAlex
W2587696209
Cited by
408
References
101
FWCI
16.95
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The Necessary Nitrogen Atom: A Versatile High-Impact Design Element for Multiparameter Optimization. https://app.cochat.ai/papers/10.1021/acs.jmedchem.6b01807
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Pennington, L. D., & Moustakas, D. T. (2017). The Necessary Nitrogen Atom: A Versatile High-Impact Design Element for Multiparameter Optimization. Journal of Medicinal Chemistry. https://doi.org/10.1021/acs.jmedchem.6b01807

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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.