Statistical Mechanics of Allosteric Enzymes
- Creators
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Einav, Tal
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Mazutis, Linas
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Phillips, Rob
Abstract
The concept of allostery in which macromolecules switch between two different conformations is a central theme in biological processes ranging from gene regulation to cell signaling to enzymology. Allosteric enzymes pervade metabolic processes, yet a simple and unified treatment of the effects of allostery in enzymes has been lacking. In this work, we take a step toward this goal by modeling allosteric enzymes and their interaction with two key molecular players—allosteric regulators and competitive inhibitors. We then apply this model to characterize existing data on enzyme activity, comment on how enzyme parameters (such as substrate binding affinity) can be experimentally tuned, and make novel predictions on how to control phenomena such as substrate inhibition.
Additional Information
© 2016 American Chemical Society. Received: February 25, 2016. Revised: April 10, 2016. Publication Date (Web): April 12, 2016. Special Issue: William M. Gelbart Festschrift. The authors thank T. Biancalani, J.-P. Changeux, A. Gilson, J. Kondev, M. Manhart, R. Milo, M. Morrison, N. Olsman, and J. Theriot for helpful discussions and insights on this paper. All plots were made entirely in Mathematica using the Custom-Ticks package.69 This work was supported in the RP group by the National Institutes of Health through DP1 OD000217 (Director's Pioneer Award) and R01 GM085286, La Fondation Pierre-Gilles de Gennes, and the National Science Foundation under Grant No. NSF PHY11-25915 at the Kavli Center for Theoretical Physics. The work was supported in the LM group by the Research and Development Program (Grant No. CH-3-SMM-01/03). We also thank the Burroughs-Wellcome Fund for its support of the Physiology Course at the Marine Biological Labratory and a postcourse research grant (LM). One of us (RP) owes his introduction to the many beautiful uses of statistical mechanics in biology to Bill Gelbart to whom this special issue is dedicated. During his inspiring career, Gelbart has been a passionate and creative developer of insights into a wide number of problems using the tools of statistical mechanics and we hope that our examples on the statistical mechanics of allosteric enzymes will please him. The authors declare no competing financial interest.Attached Files
Accepted Version - nihms857734.pdf
Supplemental Material - jp6b01911_si_001.pdf
Supplemental Material - jp6b01911_si_002.zip
Files
Additional details
- PMCID
- PMC5452729
- Eprint ID
- 66585
- Resolver ID
- CaltechAUTHORS:20160502-112340784
- NIH
- DP1 OD000217A
- NIH
- R01 GM085286
- La Fondation Pierre-Gilles de Gennes
- NSF
- PHY11-25915
- Lithuanian‐Swiss Research and Development cooperation program
- CH-3-SMM-01/03
- Burroughs-Wellcome Fund
- Created
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2016-05-02Created from EPrint's datestamp field
- Updated
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2022-04-28Created from EPrint's last_modified field