10.1021/ci700401p.s004
Aleksandr V. Marenich
Aleksandr V.
Marenich
Pei-Han Yong
Pei-Han
Yong
Isaac B. Bersuker
Isaac B.
Bersuker
James E. Boggs
James E.
Boggs
Quantitative Antidiabetic Activity Prediction for the Class of Guanidino- and
Aminoguanidinopropionic Acid Analogs Based on Electron-Conformational Studies
American Chemical Society
2008
dozen compounds
antidiabetic activity
model descriptors
guanidine group
Quantitative Antidiabetic Activity Prediction
120 compounds
oxygen atoms
aminoguanidinopropionic acid analogs
Pha flexibility
carboxyl group
training
154 compounds
topological characteristics
2008-03-24 00:00:00
Journal contribution
https://acs.figshare.com/articles/journal_contribution/Quantitative_Antidiabetic_Activity_Prediction_for_the_Class_of_Guanidino_and_Aminoguanidinopropionic_Acid_Analogs_Based_on_Electron_Conformational_Studies/2949394
The electron-conformational method has been employed to reveal the pharmacophore (Pha) and to predict
antidiabetic activity, studying 154 compounds in the class of guanidino- and aminoguanidinopropionic acid
analogs. The derived Pha consists of four sites with certain electronic and topological characteristics which
are represented by two oxygen atoms of the carboxyl group and two nitrogens of the guanidine group but
may be substituted with any other atoms that have the same electronic and geometric features. The Pha
flexibility and the influence of out-of-Pha features are described by only three model descriptors that predict
the experimental activities quantitatively within experimental uncertainty for a training set of 120 compounds.
The quality of the derived Pha and the corresponding quantitative model of activity has been validated (and
deemed acceptable) by cross-validation including many-fold cross-validations within the training set and
against an independent test set of 34 additional analogs with known experimental activities out of the training
set. At last, several dozen compounds never tested experimentally have been screened theoretically using
this model, and statistically significant hypoglycemic activities for a few of them are predicted.