Open AccessComparative study of DFT, AM1, and PM3 optimization methods modeling new psychotropic amphetamines
Author(s) -
Adelina Ion,
Mirela Praisler,
Steluţa Gosav
Publication year - 2021
Publication title -
analele universităţii "dunărea de jos" din galaţi. fascicula ii, matematică, fizică, mecanică teoretică
Language(s) - English
Resource type - Journals
eISSN - 2668-7151
pISSN - 2067-2071
DOI - 10.35219/ann-ugal-math-phys-mec.2021.1.05
Subject(s) - quantitative structure–activity relationship , molecular descriptor , computer science , biochemical engineering , computational chemistry , chemistry , biological system , machine learning , engineering , biology
In order to improve the determination of physico-chemical descriptors of organic substances, it is necessary to optimize the computational representations of their molecular structures. The computerized estimation of these descriptors is especially useful in the case of drugs of abuse, as clinical studies are not recommended for new compounds belonging to classes known to have a high toxicity. The optimization of molecular structures allows the improvement of the accuracy in determining the physico-chemical descriptors and consequently of the associated quantitative structure - property or structure - activity relationships (QSAR). We are presenting a comparative study regarding the effect of the AM1, PM3, and DFT optimization methods, which were applied in the case of a series of new psychotropic amphetamines for their physico-chemical characterization based on molecular descriptors.