Methods of machine learning and big data analysis to establish the molecular mechanisms of the effects of racetams on the metabolism of adipose tissue

Abstract

Racetams exhibit not only nootropic effects, but also affect the metabolism of fats and carbohydrates. Experimental studies have indicated the possibility of using phenylpiracetam in the treatment of obesity. At the same time, the molecular mechanisms of this pharmacological effect of phenylpiracetam are practically unknown. The paper presents the results of a new artificial intelligence (AI) method for comparative chemoreactome analysis of fonturacetam, piracetam, aniracetam, pramiracetam and levetiracetam. Another AI method, chemoneurocytological analysis, made it possible to compare the neuroprotective effects of molecules on neurons in culture. Despite the similarity of the proteomic interaction profiles of the studied molecules, differential analysis made it possible to establish the molecular mechanisms of the effect of phenylpiracetam on weight loss. Phenylpiracetam can activate β3-adrenoceptors, adenosine, glucagon-like peptide, sphingosine phosphate, and peroxisome proliferator receptors (PPARG); specifically inhibit cannabinoid, opioid, histamine, glutamate, nociceptin, neuropeptide Y and orexin receptors, which is important for normalizing appetite and improving the metabolism of adipose tissue. The synthetic AI method - pharmacoinformatic analysis indicated the advisability of taking phenylpiracetam together with vitamins C, D and group B.