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.