Allosteric proteins as logarithmic sensors

Olsman, Noah; Goentoro, Lea

doi:10.1073/pnas.1601791113

Cited by 47 publications

(45 citation statements)

References 51 publications

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“…Many natural biological sensors and controllers rely on ultrasensitivity to operate. Allosteric binding of proteins, which is known to be ultrasensitive, can be used to generate logarithmic sensors [79]. The yeast osmoregulation system combines ultrasensitivity of the MAPK pathway with negative feedback to achieve perfect adaptation [80,81,78].…”

Section: Discussionmentioning

confidence: 99%

Ultrasensitive molecular controllers for quasi-integral feedback

Samaniego

Franco

2018

Preprint

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Feedback control has enabled the success of automated technologies by mitigating the effects of variability, unknown disturbances, and noise. Similarly, feedback loops in biology reduce the impact of noise and help shape kinetic responses, but it is still unclear how to rationally design molecular controllers that approach the performance of controllers in traditional engineering applications, in particular the performance of integral controllers. Here, we describe a strategy to build molecular quasi-integral controllers by following two design principles: (1) a highly ultrasensitive response, which guarantees a small steady-state error, and (2) a tunable ultrasensitivity threshold, which determines the system equilibrium point (reference). We describe a molecular reaction network, which we name Brink motif, that satisfies these requirements by combining sequestration and an activation/deactivation cycle. We show that if ultrasensitivity conditions are satisfied, this motif operates as a quasi-integral controller and promotes homeostatic behavior of the closed-loop system (robust tracking of the input reference while rejecting disturbances). We propose potential biological implementations of Brink controllers and we illustrate different example applications with computational models.

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Section: Discussionmentioning

confidence: 99%

Ultrasensitive molecular controllers for quasi-integral feedback

Samaniego

Franco

2018

Preprint

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“…Prior studies have emphasized that a Hill equation response can act as a logarithmic sensor 3, 4 . However, a single Hill equation response provides a logarithmic sensor with limited dynamic range ( Figure 1A).…”

Section: Resultsmentioning

confidence: 99%

“…In the search for a generic circuit, my biochemical logarithmic sensor has three advantages over prior designs. First, prior models depended on particular molecular assumptions about biochemical kinetics or reaction pathways 3, 4 . My design requires only Michaelis-Menten or Hill equation responses, which are very widely observed in biochemical and cellular systems 1 .…”

Section: Resultsmentioning

confidence: 99%

A biochemical logarithmic sensor with broad dynamic range

Frank

2018

F1000Res

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Sensory perception often scales logarithmically with the input level. Similarly, the output response of biochemical systems sometimes scales logarithmically with the input signal that drives the system. How biochemical systems achieve logarithmic sensing remains an open puzzle. This article shows how a biochemical logarithmic sensor can be constructed from the most basic principles of chemical reactions. Assuming that reactions follow the classic Michaelis-Menton kinetics of mass action or the more generalized and commonly observed Hill equation response, the summed output of several simple reactions with different sensitivities to the input will often give an aggregate output response that logarithmically transforms the input. The logarithmic response is robust to stochastic fluctuations in parameter values. This model emphasizes the simplicity and robustness by which aggregate chemical circuits composed of sloppy components can achieve precise response characteristics. Both natural and synthetic designs gain from the power of this aggregate approach.

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“…Like cooperativity, allostery also modulates sensor properties. Typically, the binding of an allosteric effector to a site outside the primary ligand's binding site modulates the input-output response curve (Olsman and Goentoro, 2016) (the activation function, by our terminology). An allosteric sensor can, therefore, exist in more than one active state, e.g., k, states, each with a different activation function, h i ðxÞ (STAR Methods and Figure S1A).…”

Section: Allosteric Regulation Does Not Increase Information Capacitymentioning

confidence: 99%

The Limited Information Capacity of Cross-Reactive Sensors Drives the Evolutionary Expansion of Signaling

Komorowski

Tawfik

2019

Cell Systems

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Graphical Abstract Highlights d Cooperativity or allostery do not increase the signaling capacity d Copy number variation and cross-reactivity severely restrict signaling capacity d Duplication of cross-reactive receptors doubles capacity even with minimal divergence d Duplication with minimal divergence yields multiple crosswired signaling pathways SUMMARYSignaling systems expand by duplications of various components, be it receptors or downstream effectors. However, whether and how duplicated components contribute to higher signaling capacity is unclear, especially because in most cases, their specificities overlap. Using information theory, we found that augmentation of capacity by an increase in the copy number is strongly limited by logarithmic diminishing returns. Moreover, counter to conventional biochemical wisdom, refinements of the response mechanism, e.g., by cooperativity or allostery, do not increase the overall signaling capacity. However, signaling capacity nearly doubles when a promiscuous, non-cognate ligand becomes explicitly recognized via duplication and partial divergence of signaling components. Our findings suggest that expansion of signaling components via duplication and enlistment of promiscuously acting cues is virtually the only accessible evolutionary strategy to achieve overall high-signaling capacity despite overlapping specificities and molecular noise. This mode of expansion also explains the highly cross-wired architecture of signaling pathways. mone-receptor complexity by molecular exploitation. Science 312, 97-101.

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Allosteric proteins as logarithmic sensors

Cited by 47 publications

References 51 publications

Ultrasensitive molecular controllers for quasi-integral feedback

Ultrasensitive molecular controllers for quasi-integral feedback

A biochemical logarithmic sensor with broad dynamic range

The Limited Information Capacity of Cross-Reactive Sensors Drives the Evolutionary Expansion of Signaling

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