A sensory-computational framework to decipher and predict binary aroma interactions: A case study of furaneol with five Co-odorants

Despite the critical role of aroma interactions in shaping food flavor, their molecular mechanisms remain elusive. Here, binary interactions between furaneol and five co-odorants (guaiacol, acetylpyrazine, eugenol, 2-phenylethanol, valeric acid) with OR5M3 were investigated using an integrated sensory-computational approach. Sensory analysis classified furaneol-eugenol as synergistic, furaneol-valeric acid as masking, and the remaining pairs as additive or indifferent. Docking revealed that the synergistic pair had the most favorable binding energy (-10.11 kcal/mol), while the masking pair had the weakest (-7.95 kcal/mol). MD simulations showed synergy correlated with low RMSD and sustained H-bonds, whereas masking involved large RMSD fluctuations, fewer H-bonds. MM/PBSA quantified these differences: the synergistic complex displayed the strongest binding affinity (-23.64 kcal/mol), the masking complex the weakest (-4.24 kcal/mol) due to a large solvation penalty. This work establishes a predictive strategy based on the OR5M3 receptor model for decoding and designing aroma interactions at the molecular level.