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Robust Perfect Adaptation in Biomolecular Reaction Networks

Xiao, Fangzhou and Doyle, John C. (2018) Robust Perfect Adaptation in Biomolecular Reaction Networks. In: 2018 IEEE Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 4345-4352. ISBN 978-1-5386-1395-5. https://resolver.caltech.edu/CaltechAUTHORS:20181031-075024162

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Abstract

For control in biomolecular systems, the most basic objective of maintaining a small error in a target variable, say the expression level of some protein, is often difficult due to the presence of both large uncertainty of every type and intrinsic limitations on the controller's implementation. This paper explores the limits of biochemically plausible controller design for the problem of robust perfect adaptation (RPA), biologists' term for robust steady state tracking. It is well-known that for a large class of nonlinear systems, a system has RPA iff it has integral feedback control (IFC), which has been used extensively in real control systems to achieve RPA. However, we show that due to intrinsic physical limitations on the dynamics of chemical reaction networks (CRNs), cells cannot implement IFC directly in the concentration of a chemical species. This contrasts with electronic implementations, particularly digital, where it is trivial to implement IFC directly in a single state. Therefore, biomolecular systems have to achieve RPA by encoding the integral control variable into the network architecture of a CRN. We describe a general framework to implement RPA in CRNs and show that well-known network motifs that achieve RPA, such as (negative) integral feedback (IFB) and incoherent feedforward (IFF), are examples of such implementations. We also develop methods to designing integral feedback variables for unknown plants. This standard control notion is surprisingly nontrivial and relatively unstudied in biomolecular control. The methods developed here connect different existing fields and approaches on the problem of biomolecular control, and hold promise for systematic chemical reaction controller synthesis as well as analysis.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/CDC.2018.8619101DOIArticle
https://doi.org/10.1101/299057DOIDiscussion Paper
ORCID:
AuthorORCID
Xiao, Fangzhou0000-0002-5001-5644
Doyle, John C.0000-0002-1828-2486
Additional Information:© 2018 IEEE. The authors would like to thank Wenlong Ma and Cindy Ren for discussion and William Poole and Noah Olsman for providing feedback on the manuscript. The project was sponsored by the Defense Advanced Research Projects Agency (Agreement HR0011-16-2-0049). The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR0011-16-2-0049
Record Number:CaltechAUTHORS:20181031-075024162
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20181031-075024162
Official Citation:F. Xiao and J. C. Doyle, "Robust Perfect Adaptation in Biomolecular Reaction Networks," 2018 IEEE Conference on Decision and Control (CDC), FL, USA, 2018, pp. 4345-4352. doi: 10.1109/CDC.2018.8619101
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90530
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:01 Nov 2018 18:29
Last Modified:03 Oct 2019 20:26

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