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Modeling Neuromolecular Evolution: The Role of Nanomachines

Harry Price*, a and Ron Wallaceb

aDepartment of Chemistry, University of Central Florida,
Orlando, FL 32816-2366 USA

bDepartment of Sociology and Anthropology, University of Central Florida

This is an abstract for a presentation given at the
Eighth Foresight Conference on Molecular Nanotechnology.
There will be a link from here to the full article when it is available on the web.

 

The recent explosive growth of nanotechnology combined with advances in molecular neurobiology is creating the possibility for the evolutionary study of neuromolecular computing. A large number of biomembrane experimental studies indicate that transiently organized membrane protein-lipid arrays known as microdomains, and not the neural impulse (action potential), may be the fundamental computational unit of nerve cells. A microdomain, which typically consists of approximately one billion molecules, is generated by lipid-protein hydrophobic mismatch due to neurotransmitter binding or an electromagnetic field applied to the S4 voltage sensor of the channel protein. Lipid species with hydrophobic lengths most closely approximating that of the protein become more abundant in the protein's vicinity. Recent simulation studies conducted by the authors indicate that this self-assembly process could drive alignment of membrane ethenes in the plane of the bilayer. The latter conformation is highly conducive to ethene polarization during permeant ion movement. The consequent thermodynamic difference between the membrane microdomain and the protein tertiary structure closes the ion channel. In this way, the molecular dynamics of lipid self-assembly and ethene polarization together regulate the duration of ion-channel opening. The model is consistent with recent in vitro experiments demonstrating that channel dynamics may be directly regulated by controlled manipulation of membrane molecular structure. Viewed from a computational standpoint, microdomains thus appear to function as input-output transforms ("molecular computers") for chemical and electrical signals. The close relation of the computations to coordinated neuron signals, and hence to cognitive and behavioral function, would suggest that microdomains are adaptively significant. Accordingly, they may be expected to vary between species, as do many other molecular processes.

To investigate this possibility, we propose a research strategy linking molecular neurobiology with the engineering of computational biomimetic nanomachines embedded in hybrid systems. As a first approximation, we describe potential experiments utilizing fluorescence and Raman spectroscopies to monitor the dynamics of liposomes containing a purified ion channel during experimentally-manipulated changes in membrane unsaturated-lipid composition. The goals of these experiments would be to demonstrate lipid self-assembly and ethene polarization during permeant ion movement, and to correlate these process with the duration of the open-channel state. A second set of experiments would spectroscopically monitor molecular processes in liposomal models of microdomains based on species-specific saturated-to-unsaturated lipid ratios. It is anticipated that species systems with higher computational power would be characterized by a more efficient conversion of molecular computations into neuron frequency codes. These findings could be modeled by means of molecular biomimetic devices possibly composed of materials not occurring in natural microdomains but nonetheless conserving their electromechanical properties. Such devices would minimally include a bounded molecular matrix with polarizable elements and a component (molecular wire) which conducts electrons when activated by an appropriate input signal (voltage, photons). Variations in species-specific lipid ratios would be modeled as quantitative variations in polarizable elements within the molecular matrix. It is suggested that the combined use of liposomal and nanomachine models of neural membrane microdomains would make a significant contribution to the study of brain evolution.


*Corresponding Address:
Harry Price, Department of Chemistry, University of Central Florida
4000 Central Florida Boulevard
Orlando, FL 32816-2366 USA
Email: hprice@pegasus.cc.ucf.edu



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