This invention discloses a method for screening
odor inhibitors based on olfactory receptors and intermolecular interactions in the field of deodorization technology. The method includes: using an
olfactory receptor database, multi-level screening or
machine learning to predict olfactory receptors that a target
odor pollutant can bind to or activate; multi-level screening or
machine learning to predict potential inhibitors of the olfactory receptors; calculating the
binding energy between the olfactory receptors and the target
odor pollutant, and the screened or predicted inhibitors; preferentially selecting potential inhibitors with binding energies lower than those of the target odor
pollutant; and using an electronic
nose to test the odor-reducing effect of the potential inhibitors on the target odor pollutant. This invention proposes a
screening method for odor inhibitors from the perspective of olfactory mechanisms. By utilizing the competitive and inhibitory effects of substances on olfactory receptors, it weakens the olfactory response of the target odor pollutant, thereby achieving the effect of odor suppression. Compared with manual olfactory screening methods, this method can effectively improve the development efficiency of deodorants and reduce
workload, cost, and health risks.