Automated QM/MM Screening of Rhodopsin Variants with Enhanced Fluorescence

Abstract

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, , 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.

Picosecond quantum-classical dynamics reveals that the coexistence of light-induced microbial and animal chromophore rotary motion modulates the isomerization quantum yield of heliorhodopsin

“…The computational models employed for bovine rhodopsin and thermoplasmatales archaeon rhodopsin were constructed with the a-ARM QM/MM model building protocol, 40,41 implemented in the PyARM software package, 11,42 starting from their crystallographic structures resolved at 2.4 Å (Protein Data Bank code: 1U19) 72 and 2.2 Å (Protein Data Bank code: 6IS6), 34 respectively. Such models were used to simulate two room temperature Boltzmann-like distributions and extract 200 initial conditions for each rhodopsin at room temperature following a previously reported protocol.…”

“…2C and D, the constructed TaHeR and Rh models yielded FC vertical excitation energies (here expressed in terms of absorption maxima, l a max ) only 12 nm blue shifted (530 nm) and 1 nm red shifted (499 nm) relative to the observed values, respectively. Furthermore, by using the wild-type QM/MM models as starting point for constructing a set of mutant models, 44 it was possible to reproduce the trend in the observed l a max displayed by a set of single mutants of Rh, 41 and a set of single and double mutants of TaHeR (in most cases with a blue-shifted error typical of a-ARM models 10,11,41,[43][44][45] ). The glutamic-to-aspartic acid mutation at the 108 counterion position of TaHeR yielded identical l a max value with respect to the wild-type, again in line with the observation.…”

Automatic Rhodopsin Modeling with Multiple Protonation Microstates

“…The ARM protocol aims to automate the generation of QM/MM models for rhodopsin proteins designed to qualitatively reproduce λ max changes. The protocol has been thoroughly described in the literature; , In what follows, we will only provide a brief overview of the methodology. Figure shows a scheme summarizing the ARM protocol, which is subdivided into two parts: the ARM input generator (Figure , green), which generates a formatted PDB file containing the structure of the rhodopsin of interest with the appropriate protonation states for all of its titratable residues and the necessary counterions, and the QM/MM model generator, which partially relaxes the rhodopsin structure before calculating the desired λ max as well as more complex properties.…”

“…The Automatic Rhodopsin Modeling (ARM) simulation protocol , aims at automating the construction of QM/MM models for rhodopsin proteins. In practice, ARM requires as inputs only a rhodopsin crystallographic structure and the desired pH value.…”

Engineered blue-shifted melanopsins for subcellular optogenetics

“…Given the complexity of such models, this is a time-consuming and error-prone process. For these reasons, some authors were involved in developing a technology called Automatic Rhodopsin Modeling (ARM) for the automated construction of congruent opsin QM/MM models 41 . Here, we show the use of homology modeling and ARM, together with molecular engineering and live cell imaging approaches, to develop spectrally blue-shifted, bistable mMeOp mutants, and their applications in controlling subcellular signaling and cell behavior.…”