Predictive analysis of the properties of autophagy inducers in reproductive and developmental toxicity

<p>1 / 1Predictive analysis of the properties of autophagy inducers in reproductive and developmental toxicity</p><p></p><p>Introduction:Since dysfunction of the autophagy pathway is involved in the pathogenesis of many diseases under chemical-induced stress conditions, it is necessary to investigate whether autophagy-inducing substances affect the dysfunction of this pathway. Therefore, in this study, autophagy inducers with specific activity were estimated by multivariate feature extraction of autophagy inducers and known toxicants.</p><p>Methods:A total of 121 chemicals with reported genetic and pharmacological modulation of autophagy, chemicals with reported teratogenicity by the U.S. Food and Drug Administration (FDA), and chemicals with known toxicity to adults were collected from PubChem, and ADMET predictor 9.5 was used to extract data on drug metabolism. The data were generated by extracting the Michaelis-Menten constant, Vmax, and clearance for the 11 CYP450 subtypes involved in drug metabolism using ADMET predictor 9.5. Principal component analysis and clustering, which are multivariate analyses, were performed on the generated data.</p><p>Results:Principal component analysis of 11 CYP450 subtypes with respect to 121 chemicals showed that 4 chemicals had different contribution rates than the others. Among them, mycolactone was extracted as an autophagy inducer; the clustering of the 11 CYP450 subtypes resulted in a hierarchy of 6 chemicals, in the same cluster as ibuprofen and valproic acid, which are known teratogenic chemicals docosahexaenoic acid and betulinic acid were extracted. These results suggest that autophagy-inducing substances may have specific activity against CYP450.</p>