Computational approaches for decoding structure-saltiness enhancement and aroma perception mechanisms of odorants: From machine learning to molecular simulation.
Journal:
Food research international (Ottawa, Ont.)
PMID:
39967096
Abstract
The unclear relationship between structure and saltiness enhancement limits the development and application of savory odorants. The structure characteristic-saltiness enhancement perception (SEP) mechanisms of savory odorants were investigated by machine learning, molecular docking, and site-directed mutagenesis simulations. The XGBoost model (R = 0.96) showed better prediction on the maximum saltiness-enhancement ability of odorants based on their structures. The important features of the odorants contributing to SEP were analyzed by Shapley additive explanations (SHAP). Results showed that phenyl and aldehyde groups had significant positive contributions to SEP, with SHAP values of + 2.94 and + 0.74, respectively. Molecular docking and site-directed mutagenesis simulations elucidated the interaction region, forces, and key sites between savory odorants and olfactory receptors. Results showed TM3, TM5 and TM6 were the main interaction regions of the savory odorants prioritize binding with OR1A1 and OR1D2, resulting in the characteristic aromas. Hydrogen bonding and hydrophobic interactions were the key driving forces. Phe203, Asn109, and Asn155 of OR1A1 were partially important residues involved in the interactions with savory odorants. These findings presented a quick screening approach for savory odorants and revealed their SEP mechanism, providing theoretical guidance to facilitate the application of odor-induced salt reduction in food industry.