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Abstract

A deterministic model is presented for predicting the passive and stimuli-responsive characteristics of biomolecular networks. These biomolecular networks consist of multiple bilayer interfaces that can incorporate stimuli-responsive molecules such as peptides and proteins. A model is presented and a lumped parameter method is used to obtain the network equations for several case studies. The model is then utilized to predict the response of a biomolecular network that exhibits rectification behavior due to the presence of voltage-responsive protein incorporated into the interfacial bilayer. This article demonstrates the electric response of systems of biomolecular networks and prompts further research into their use for engineering applications.

Keywords

Bio-inspired optimization sensor

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References

Aksimentiev

Schulten

(2005) Imaging [alpha]-hemolysin with molecular dynamics: ionic conductance, osmotic permeability, and the electrostatic potential map. Biophysical Journal 88(6): 3745–3761.

Brenan

Campbell

Petzold

. (1996) Numerical Solution of Initial-Value Problems in Differential-Algebraic Equations, vol. 14. Philadelphia, PA: Society for Industrial and Applied Mathematics.

Cheng

Lin

Bellin

. (2010) Probing localized neural mechanotransduction through surface-modified elastomeric matrices and electrophysiology. Nature Protocols 5: 714–724.

Gouaux

(1998) α-Hemolysin from Staphylococcus aureus: an archetype of beta-barrel, channel-forming toxins. Journal of Structural Biology 121(2): 110–122.

Hodgkin

Huxley

Katz

(1952) Measurement of current-voltage relations in the membrane of the giant axon of Loligo. Journal of Physiology 116: 424–448.

Holden

Needham

Bayley

(2007) Functional bionetworks from nanoliter water droplets. Journal of the American Chemical Society 129(27): 8650–8655.

Kuhlman

Dantas

Ireton

. (2003) Design of a novel globular protein fold with atomic-level accuracy. Science 302(5649): 1364–1368.

Kunkel

Mehrmann

(2006) Differential-Algebraic Equations: Analysis and Numerical Solution. European Mathematical Society. Zürich, Switzerland

Lin

Cheng

Leduc

. (2009) Understanding sensory nerve mechanotransduction through localized elastomeric matrix control. PLoS One 4: 1–9.

10.

Maglia

Heron

Hwang

. (2009) Droplet networks with incorporated protein diodes show collective properties. Nature Nanotechnology 4: 437–440.

11.

Park

Cochran

(2009) Protein Engineering and Design, vol. 75. Boca Raton, FL: CRC Press.

12.

Sarles

Leo

(2010) Physical encapsulation of droplet interface bilayers for durable, portable biomolecular networks. Lab on a Chip 10(6): 710–717.

13.

Sarles

Leo

(2011) Membrane-based biomolecular smart materials. Smart Materials and Structures 20: 1–12.

14.

Sarles

Madden

Leo

(2011) Hair cell inspired mechanotransduction with a gel-supported, artificial lipid membrane. Soft Matter 7: 4644–4653.

15.

Shirvani

Joseph

WHS

(1998) Solutions of linear differential algebraic equations. SIAM Review 40: 344–346.

16.

Sundaresan

Leo

(2010) Chemoelectrical energy conversion of adenosine triphosphate using ATPases. Journal of Intelligent Material Systems and Structures 10: 201–212.

17.

Tzima

Irani-Tehrani

Kiosses

. (2005) A mechanosensory complex that mediates the endothelial cell response to fluid shear stress. Nature 437: 426–431.

18.

Sigworth

LaVan

(2010) Synthetic protocells to mimic and test cell function. Advanced Materials 22(1): 120–127.

Deterministic model of biomolecular networks with stimuli-responsive properties

Abstract

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References