# Computationally Driven Design of De Novo Genetically Encoded Voltage Indicators

> **NIH NIH F30** · UNIVERSITY OF PENNSYLVANIA · 2020 · $50,016

## Abstract

PROJECT SUMMARY:
Simultaneous optical monitoring of the electrical activity of hundreds of neurons with single-cell fidelity
comparable to whole-cell patch clamp electrophysiology would enable recording of the circuit-level activity that
gives rise to affect, behavior, and cognition and would drive novel insights into the network dysregulation
underlying psychiatric and neurological disorders. Therefore, enormous effort has been expended on designing
genetically encoded voltage indicators (GEVIs), cell-type specific protein reporters that transduce changes in
membrane potential as a fluorescent signal. Large-scale adoption of GEVIs is dependent on them possessing
the brightness, voltage-sensitivity, and temporal resolution to allow for the in vivo recording of high frequency
bursts, the monitoring of sub-threshold voltage dynamics, and the accurate reconstruction of action potential
waveforms. Current GEVIs, such as those constructed from archaerhodopsin, do not possess all these desired
properties and are intrinsically limited in their temporal resolution due to their reliance on structural
rearrangements for signal transduction. We propose the construction of high temporal resolution GEVIs by
leveraging validated methods in computational de novo protein design to produce transmembrane helical
bundle proteins that bind a near-infrared fluorescent, mammalian-endogenous biliverdin chromophore. Proper
positioning of biliverdin within the protein will allow for optical
voltage-reporting by the Stark effect, an
intrinsically voltage-sensitive phenomenon wherein an electric field acting upon a chromophore causes sub-
picosecond changes in fluorescence by altering absorbance. This work will produce near-infrared fluorescent,
high temporal resolution voltage probes permitting new insights into the circuit-level physiology underlying the
complex phenotypes seen in the normal and diseased brain.

## Key facts

- **NIH application ID:** 9907495
- **Project number:** 1F30MH122076-01
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Ivan Kuznetsov
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $50,016
- **Award type:** 1
- **Project period:** 2020-01-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9907495

## Citation

> US National Institutes of Health, RePORTER application 9907495, Computationally Driven Design of De Novo Genetically Encoded Voltage Indicators (1F30MH122076-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9907495. Licensed CC0.

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