Choosing relevant functional groups for optimizing Artificial Neural Networks detecting NBOMe hallucinogens

  • Adelina Ion "Dunarea de Jos" University of Galati, Romania
  • Steluța Gosav "Dunarea de Jos" University of Galati, Romania
  • Mirela Praisler "Dunarea de Jos" University of Galati, Romania https://orcid.org/0000-0003-0936-4399
DOI: https://doi.org/10.35219/ann-ugal-math-phys-mec.2019.2.06
Keywords: NBOMe psychedelic phenethylamines, functional groups, Artificial Neural Networks

Abstract

In  the early 2010s,  a new group of  illicit psychedelic phenethylamines  was reported by the law enforcement agencies,  namely  the  NBOMe hallucinogens. The latter seem to be sold on the black  market as an alternative to LSD, due to their  powerful  psychoactive effects. The goal of  this study was to develop an  optimized Artificial Neural Network (ANN) able  to classify NBOMe hallucinogens based on their functional groups. These chosen molecular descriptors (functional groups) have been computed, by using the Dragon 5.5 program, for  the molecular structures of the main  NBOMe hallucinogens, which have been first optimized by using the Hyperchem program.  The  ANN system  was  built with the Easy NN plus program. Then, the importance of each functional group has been assessed. A new input database has been built with the functional groups found to be the most important.The performance of the new ANN system  has been characterized  based on  several classification accuracy criteria. The impact of the variable selection on the ANN performances  is discussed in detail.

Author Biographies

Adelina Ion, "Dunarea de Jos" University of Galati, Romania

Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment,

 „Dunărea de Jos” University of Galati, Romania 

Steluța Gosav, "Dunarea de Jos" University of Galati, Romania

Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment,

 „Dunărea de Jos” University of Galati, Romania ;

INPOLDE interdisciplinary research network, ReForm multidisciplinary Platform, Dunarea de Jos University of Galati, Faculty of Sciences and Environment, 111 Domneasca St., 800201 Galati, Romania.

Mirela Praisler, "Dunarea de Jos" University of Galati, Romania

Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment,

 „Dunărea de Jos” University of Galati, Romania 

Published
2019-11-28
How to Cite
Ion, A., Gosav, S. and Praisler, M. (2019) “Choosing relevant functional groups for optimizing Artificial Neural Networks detecting NBOMe hallucinogens”, Analele Universității ”Dunărea de Jos” din Galați. Fascicula II, Matematică, fizică, mecanică teoretică / Annals of the ”Dunarea de Jos” University of Galati. Fascicle II, Mathematics, Physics, Theoretical Mechanics, 42(2), pp. 160-166. doi: https://doi.org/10.35219/ann-ugal-math-phys-mec.2019.2.06.
Issue
Vol 42 No 2 (2019)
Section
Articles

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