Published July 26, 2016 | Version Published + Supplemental Material
Journal Article Open

Allosteric proteins as logarithmic sensors

  • 1. ROR icon California Institute of Technology

Abstract

Many sensory systems, from vision and hearing in animals to signal transduction in cells, respond to fold changes in signal relative to background. Responding to fold change requires that the system senses signal on a logarithmic scale, responding identically to a change in signal level from 1 to 3, or from 10 to 30. It is an ongoing search in the field to understand the ways in which a logarithmic sensor can be implemented at the molecular level. In this work, we present evidence that logarithmic sensing can be implemented with a single protein, by means of allosteric regulation. Specifically, we find that mathematical models show that allosteric proteins can respond to stimuli on a logarithmic scale. Next, we present evidence from measurements in the literature that some allosteric proteins do operate in a parameter regime that permits logarithmic sensing. Finally, we present examples suggesting that allosteric proteins are indeed used in this capacity: allosteric proteins play a prominent role in systems where fold-change detection has been proposed. This finding suggests a role as logarithmic sensors for the many allosteric proteins across diverse biological processes.

Additional Information

© 2016 National Academy of Sciences. Freely available online through the PNAS open access option. Edited by Taekjip Ha, University of Illinois at Urbana–Champaign, Urbana, IL, and approved May 16, 2016 (received for review February 1, 2016). Published online before print July 7, 2016. We thank Kibeom Kim, Christopher Frick, Harry Nunns, Michael Abrams, Ty Basinger, Enoch Yeung, Tal Einav, Nicholas Frankel, Rob Phillips, and Henry Lester for discussions and suggestions on the manuscript. We also thank Meritxell Canals and Arthur Christopoulos for sharing their raw experimental data on allostery in GPCRs. This work was supported by the Benjamin M. Rosen Fellowship (N.O.), James S. McDonnell Scholar Award in Complex Systems 220020365 (to L.G.), and NSF CAREER Award NSF.145863 (to L.G.). Author contributions: N.O. and L.G. designed research; N.O. performed research; N.O. analyzed data; and N.O. and L.G. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1601791113/-/DCSupplemental.

Attached Files

Published - PNAS-2016-Olsman-E4423-30.pdf

Supplemental Material - pnas.201601791SI.pdf

Files

PNAS-2016-Olsman-E4423-30.pdf

Files (2.6 MB)

Name Size
md5:81a6f41eea2fa1fb9df697e75a0259ca
1.4 MB Preview Download
md5:ff643c2ce410442debcf6d4e1bf26125
1.2 MB Preview Download

Additional details

Identifiers

PMCID
PMC4968753
Eprint ID
68903
Resolver ID
CaltechAUTHORS:20160708-072507691

Funding

Benjamin M. Rosen Fellowship
James S. McDonnell Foundation
220020365
NSF
MCB-1453863

Dates

Created
2016-07-08
Created from EPrint's datestamp field
Updated
2022-04-26
Created from EPrint's last_modified field