Quantum computing approach helps create targeted optogenetic proteins

The quantum computing simulation generated a list of protein variants that qualify as potential optogenetic tools.

The research done at Ruhr University Bochum could help manufacture optogenetic tools in a targeted manner.
The research done at Ruhr University Bochum could help manufacture optogenetic tools in a targeted manner.
RUB, Kramer

A Ruhr University Bochum (RUB; Bochum, Germany) research team has developed a strategy for designing light-sensitive proteins that have use in optogenetics. These proteins can be switched on and off through light impulses, thus triggering specific cellular processes. They can, for example, be used to analyze and control how signals are transmitted by nerve cells. So far, researchers developing optogenetic proteins have been forced to resort to trial-and-error, but the RUB team's approach combines computer-aided and experimental methods to enable more targeted proteins.

In collaboration with a colleague from the University of Münster (Münster, Germany), the research team is led by Professor Stefan Herlitze, Department of General Zoology and Neurobiology at RUB, and Professor Klaus Gerwert, Department of Biophysics at RUB.(L-R) Klaus Gerwert and Till Rudack.(L-R) Klaus Gerwert and Till Rudack.RUB, Kramer 

An example of an optogenetic tool is the protein melanopsin. It can be switched on and off by two light signals in different colors. "Often, more than just one optogenetic tool is requiredfor example, if two different processes have to be controlled in a cell independently of each other," explains Raziye Karapinar from the Department of General Zoology and Neurobiology. "We must therefore ensure that the color signals for both tools do not overlap," adds Dr. Till Rudack, a biophysicist from RUB. 

Related: Spectroscopy method helps detect deactivation mechanism for switch proteins

Gerwert's and Herlitze's research team has developed a hybrid strategy for targeted protein engineering of melanopsin and other optogenetic tools. To this end, the researchers combined computer-aided calculating methods with electrophysiological measurements. 

Using quantum computing simulations, they calculated the specific light color required to activate a protein, allowing them to determine how individual protein building blocks that respond to the exchange of individual protein building blocks affects the light color. The computer simulation generated a list of protein variants that qualify as potential optogenetic tools. Subsequently, the researchers used electrophysiological measurements to analyze the promising candidates with regard to their optogenetic potential. This includes light sensitivitythat is, how much light is needed to switch the protein on and off, as well as the speed and selectivity at which mechanisms are implemented or terminated after the activation of the switch. A good optogenetic tool can be switched on and off in quick succession at low light intensity.(L-R) Raziye Karapinar and Stefan Herlitze.(L-R) Raziye Karapinar and Stefan Herlitze.RUB, Kramer 

Using the well-researched optogenetic tool channelrhodopsin-2, the team validated the new hybrid strategy. For this protein, the researchers used computer simulation to verify how an exchange of protein building blocks would affect the activating light color. The prognoses corresponded with the values measured in experiments. "This match shows how reliable our strategy is, and it also validates its application for proteins about which we don't know much, such as melanopsin," says biophysicist Dr. Stefan Tennigkeit.  

With their strategy, the group exchanged specific protein building blocks in melanopsin, thus manipulating the light color for molecule activation, without impairing the protein function. The light color that activates the usual melanopsin version overlaps with that of many other optogenetic toolswhich is why they cannot be used in combination. "I'm convinced that it will be possible to combine this new melanopsin variant with other optogenetic tools in future, in order to control complex cellular processes," says Herlitze. 

"Unlike traditional protein engineering methods based on trial and error, our approach saves a lot of time thanks to automated computer-aided prognoses that can be calculated on several computers at the same time," concludes Gerwert. 

Full details of the work appear in the journal ChemBioChem.

More in Biophotonics Techniques