Computational design of a modular protein sense-response system.

Autor: Glasgow AA; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA., Huang YM; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA., Mandell DJ; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.; Bioinformatics Graduate Program, University of California San Francisco, San Francisco, CA, USA., Thompson M; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA., Ritterson R; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA., Loshbaugh AL; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.; Biophysics Graduate Program, University of California San Francisco, San Francisco, CA, USA., Pellegrino J; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.; Biophysics Graduate Program, University of California San Francisco, San Francisco, CA, USA., Krivacic C; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.; UC Berkeley-UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA, USA., Pache RA; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA., Barlow KA; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.; Bioinformatics Graduate Program, University of California San Francisco, San Francisco, CA, USA., Ollikainen N; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.; Bioinformatics Graduate Program, University of California San Francisco, San Francisco, CA, USA., Jeon D; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA., Kelly MJS; Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA., Fraser JS; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.; Biophysics Graduate Program, University of California San Francisco, San Francisco, CA, USA.; Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, USA., Kortemme T; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA. tanjakortemme@gmail.com.; Bioinformatics Graduate Program, University of California San Francisco, San Francisco, CA, USA.; Biophysics Graduate Program, University of California San Francisco, San Francisco, CA, USA.; UC Berkeley-UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA, USA.; Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, USA.; Chan Zuckerberg Biohub, San Francisco, CA, USA.
Jazyk: angličtina
Zdroj: Science (New York, N.Y.) [Science] 2019 Nov 22; Vol. 366 (6468), pp. 1024-1028.
DOI: 10.1126/science.aax8780
Abstrakt: Sensing and responding to signals is a fundamental ability of living systems, but despite substantial progress in the computational design of new protein structures, there is no general approach for engineering arbitrary new protein sensors. Here, we describe a generalizable computational strategy for designing sensor-actuator proteins by building binding sites de novo into heterodimeric protein-protein interfaces and coupling ligand sensing to modular actuation through split reporters. Using this approach, we designed protein sensors that respond to farnesyl pyrophosphate, a metabolic intermediate in the production of valuable compounds. The sensors are functional in vitro and in cells, and the crystal structure of the engineered binding site closely matches the design model. Our computational design strategy opens broad avenues to link biological outputs to new signals.
(Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
Databáze: MEDLINE
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