PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 1, 1982Journal of Medicinal Chemistry144 citations

Potential antitumor agents. 36. Quantitative relationships between experimental antitumor activity, toxicity, and structure for the general class of 9-anilinoacridine antitumor agents

View Full Paper
WDWilliam A. DennyBCBruce F. CainGAGraham J. Atwell

Key Points

Key points are not available for this paper at this time.

Abstract

Quantitative relationships (QSAR) have been derived between antileukemic (L1210) activity and agent physicochemical properties for 509 tumor-active members of the general class of 9-anilinoacridines. One member of this class is the clinical agent m-AMSA (NSC 249992). Agent hydrophobicity proved a significant but not a dominant influence on in vivo potency. The electronic properties of substituent groups proved important, but the most significant effects on drug potency were shown by the steric influence of groups placed at various positions on the 9-anilinoacridine skeleton. The results are entirely consistent with the physiologically important step in the action of these compounds being their binding to double-stranded DNA by intercalation of the acridine chromophore between the base pairs and positioning of the anilino group in the minor groove, as previously suggested. An equation was also derived for the acute toxicities of 643 derivatives of 9-anilinoacridine. This equation took a somewhat similar form to the one modeling antileukemia potency, emphasizing the usual fairly close relationship between potency and acute toxicity for antitumor agents in general. This study demonstrated the power of QSAR techniques to structure very large amounts of biological data and to allow the extraction of useful information from them bearing on the possible site of action of the compounds concerned.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Denny et al. (1982) studied this question.

synapsesocial.com/papers/6a70c8728031ec7bb1dc930fhttps://doi.org/10.1021/jm00345a015
Ask AI
Helpful
Bookmark
Share
View Full Paper