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Computationally Driven Design of De Novo Genetically Encoded Voltage Indicators

Computationally Driven Design of De Novo Genetically Encoded Voltage Indicators
De Novo 基因编码电压指示器的计算驱动设计
批准号:
10556358
负责人:
Ivan Kuznetsov
金额:
$1.59万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-01-01 至 2023-05-15

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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.
期刊论文(10)
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科研奖励(0)
会议论文
DOI: 10.1016/j.mbs.2021.108754
发表时间: 2022-03
期刊: Mathematical biosciences
影响因子: 4.3
作者: [Kuznetsov IA, Kuznetsov AV]
通讯作者: Kuznetsov AV
DOI: 10.1016/j.mbs.2020.108468
发表时间: 2020-11
期刊: Mathematical biosciences
影响因子: 4.3
作者: [Kuznetsov IA, Kuznetsov AV]
通讯作者: Kuznetsov AV
An analytical solution simulating growth of Lewy bodies.
模拟路易体生长的解析解。
DOI: 10.1093/imammb/dqac006
发表时间: 2022
期刊: Mathematical medicine and biology : a journal of the IMA
影响因子: --
作者: [Kuznetsov,IvanA, Kuznetsov,AndreyV]
通讯作者: Kuznetsov,AndreyV
DOI: 10.1002/cnm.3648
发表时间: 2022-11
期刊: INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
影响因子: 2.1
作者: [Kuznetsov, Ivan A., Kuznetsov, Andrey, V]
通讯作者: Kuznetsov, Andrey, V
Computationally Driven Design of De Novo Genetically Encoded Voltage Indicators
  • 批准号:
    10326360
  • 项目类别:
  • 资助金额:
    $3.42万
  • 财政年份:
    2020
  • 负责人:
    Ivan Kuznetsov
  • 依托单位:
Computationally Driven Design of De Novo Genetically Encoded Voltage Indicators
  • 批准号:
    9907495
  • 项目类别:
  • 资助金额:
    $5.0万
  • 财政年份:
    2020
  • 负责人:
    Ivan Kuznetsov
  • 依托单位:
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