Computer-Aided Methods for Molecular Classification

The study aims to analyze the degree of similarity of some molecules belonging to two subgroups of Aminoalkylindoles. After extracting the molecules’ characteristics using Cheminformatics methods, and the computation of the Tanimoto coefficients, dendrograms and heatmaps were built to reveal the deg...

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Bibliographic Details
Main Authors: Alina Bărbulescu, Lucica Barbeș, Cristian Ștefan Dumitriu
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/10/9/1543
Description
Summary:The study aims to analyze the degree of similarity of some molecules belonging to two subgroups of Aminoalkylindoles. After extracting the molecules’ characteristics using Cheminformatics methods, and the computation of the Tanimoto coefficients, dendrograms and heatmaps were built to reveal the degree of similarity of the analyzed drugs. Some atom-pair similarities between the molecules in the same group were detected. The clusters determined by the k-means method divided the Benzoylindoles into two subgroups but kept all the Phenylacetylindoles together in the same set. The activity spectrum of the elements in each group was also analyzed, and similarities have been emphasized. The clustering has been validated using the Kruskal–Wallis test on the series of computed probabilities of the main effects.
ISSN:2227-7390