Computational analysis of umami and bitter taste interactions: orthogonality in receptor–ligand binding

Abstract

We investigated the in silico binding of ligands relevant to the bitter taste in wine (flavan-3-ol) and the umami taste (glutamate) with bitter and umami receptors (T1R1 and T2R). The binding energies for the binding sites of the receptors were calculated via molecular docking simulation and validated via molecular dynamics simulation. As expected, bitter ligands have high affinity for T2R, and umami ligands have high affinity for T1R1. We build an affinity matrix (the “taste matrix”) P_ij and discuss the dimensionality of the taste dataspace formed by these ligands in analogy with the RGB color vision space. The redundancy among the taste receptors can be treated mathematically as a linear dependency of columns and rows in the ligand–receptor interaction matrix, which we call the “taste matrix.” We suggest a formula, D = rank(P_ij)−1, for the dimensionality of this taste dataspace (the number of linearly independent columns and rows) and calculate D = 3 for the taste determined by T1R1 and T2R. Given that bitterness forms a 2D dataspace, this result is consistent with the notion that umami taste is orthogonal to bitterness.