RESUMEN
We propose a quantitative structure-property relationship (QSPR) model for prediction of spectral tuning in cyan, green, orange, and red fluorescent proteins, which are engineered by motifs of the green fluorescent protein. Protein variants, in which their chromophores are involved in the π-stacking interaction with amino acid residues tyrosine, phenylalanine, and histidine, are prospective markers useful in bioimaging and super-resolution microscopy. In this work, we constructed training sets of the π-stacked complexes of four fluorescent protein chromophores (of the green, orange, red, and cyan series) with various substituted benzenes and imidazoles and tested the use of dipole moment variation upon excitation (DMV) as a descriptor to evaluate the vertical excitation energies in these systems. To validate this approach, we computed and analyzed electron density distributions of the π-stacked complexes and correlated the QSPR predictions with the reference values of the transition energies obtained using the high-level ab initio quantum chemistry methods. According to our results, the use of the DMV descriptor allows one to predict excitation energies in the π-stacked complexes with errors not exceeding 0.1 eV, which makes this model a practically useful tool in the development of efficient fluorescent markers for in vivo imaging.