Adaptation of Empirical Methods to Predict the LogD of Triazine Macrocycles.
Journal
ACS medicinal chemistry letters
ISSN: 1948-5875
Titre abrégé: ACS Med Chem Lett
Pays: United States
ID NLM: 101521073
Informations de publication
Date de publication:
12 Oct 2023
12 Oct 2023
Historique:
received:
03
07
2023
accepted:
01
09
2023
pmc-release:
12
10
2024
medline:
18
10
2023
pubmed:
18
10
2023
entrez:
18
10
2023
Statut:
epublish
Résumé
Octanol/water partition coefficients guide drug design, but algorithms do not always accurately predict these values. For cationic triazine macrocycles that adopt a conserved folded shape in solution, common algorithms fall short. Here, the logD values for 12 macrocycles differing in amino acid choice were predicted and then measured experimentally. On average, AlogP, XlogP, and ChemAxon predictions deviate by 0.9, 2.8, and 3.9 log units, with XlogP overestimating lipophilicity and AlogP and ChemAxon underestimating lipophilicity. Importantly, however, a linear relationship (
Identifiants
pubmed: 37849549
doi: 10.1021/acsmedchemlett.3c00290
pmc: PMC10577694
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1378-1382Informations de copyright
© 2023 American Chemical Society.
Déclaration de conflit d'intérêts
The authors declare no competing financial interest.
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