Open AccessComputer-Aided Classification of New Psychoactive Substances
Author(s) -
Alina Bărbulescu,
Lucica Barbeș,
Cristian Ștefan Dumitriu
Publication year - 2021
Publication title -
journal of chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.436
H-Index - 50
eISSN - 2090-9063
pISSN - 2090-9071
DOI - 10.1155/2021/4816970
Subject(s) - cheminformatics , chemistry , similarity (geometry) , quantitative structure–activity relationship , dendrogram , cluster analysis , molecular descriptor , artificial intelligence , pattern recognition (psychology) , computational chemistry , stereochemistry , computer science , population , demography , sociology , genetic diversity , image (mathematics)
The appearance on the free market of synthetic cannabinoids raised the researchers’ interest in establishing their molecular similarity by QSAR analysis. A rigorous criterion for classifying drugs is their chemical structure. Therefore, this article presents the structural similarity of two groups of drugs: benzoylindoles and phenylacetylindoles. Statistical analysis and clustering of the molecules are performed based on their numerical characteristics extracted using Cheminformatics methods. Their similarities/dissimilarities are emphasized using the dendrograms and heat map. The highest discrepancies are found in the phenylacetylindoles group.