Automated QM/MM Screening of Rhodopsin Variants with Enhanced Fluorescence

We present a computational protocol for the fast and
automated
screening of excited-state hybrid quantum mechanics/molecular mechanics
(QM/MM) models of rhodopsins to be used as fluorescent probes based
on the automatic rhodopsin modeling protocol (a-ARM).
Such “a-ARM fluorescence screening protocol”
is implemented through a general Python-based driver, PyARM, that is also proposed here. The implementation and performance
of the protocol are benchmarked using different sets of rhodopsin
variants whose absorption and, more relevantly, emission spectra have
been experimentally measured. We show that, despite important limitations
that make unsafe to use it as a black-box tool, the protocol reproduces
the observed trends in fluorescence and it is capable of selecting
novel potentially fluorescent rhodopsins. We also show that the protocol
can be used in mechanistic investigations to discern fluorescence
enhancement effects associated with a near degeneracy of the S1/S2 states or, alternatively, with a barrier generated
via coupling of the S0/S1 wave functions.