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Nature Biotechnology
Article
License: implied-oa
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PubMed Central
Other literature type . 2019
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Nature Biotechnology
Article . 2019 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Multi-input chemical control of protein dimerization for programming graded cellular responses

Authors: David Baker; William Sheffler; Katrina M Warner; Cindy T. Wei; Per Jr Greisen; Per Jr Greisen; Daniel Cunningham-Bryant; +6 Authors

Multi-input chemical control of protein dimerization for programming graded cellular responses

Abstract

Chemical and optogenetic methods for post-translationally controlling protein function have enabled modulation and engineering of cellular functions. However, most of these methods only confer single-input, single-output control. To increase the diversity of post-translational behaviors that can be programmed, we built a system based on a single protein receiver that can integrate multiple drug inputs, including approved therapeutics. Our system translates drug inputs into diverse outputs using a suite of engineered reader proteins to provide variable dimerization states of the receiver protein. We show that our single receiver protein architecture can be used to program a variety of cellular responses, including graded and proportional dual-output control of transcription and mammalian cell signaling. We apply our tools to titrate the competing activities of the Rac and Rho GTPases to control cell morphology. Our versatile tool set will enable researchers to post-translationally program mammalian cellular processes and to engineer cell therapies.

Keywords

Models, Molecular, Protein Conformation, Proteins, Article, Cell Line, Optogenetics, Mice, Drug Design, NIH 3T3 Cells, Animals, Combinatorial Chemistry Techniques, Humans, Synthetic Biology, Protein Multimerization, Protein Processing, Post-Translational, HeLa Cells, Signal Transduction

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    76
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
76
Top 1%
Top 10%
Top 1%
Green
hybrid