4.11 What Next: Toward a Biomolecular Computer?


4.11 What Next: Toward a Biomolecular Computer?

Prediction of the future seems to be quite often more of a complacent pastime than an activity producing useful results. Too many presently unknown factors might dramatically change contemporary, seemingly reliable tendencies. Let us try therefore to consider the state of the art in the field of information processing capabilities of reaction-diffusion systems. Let us discuss the new experimental and theoretical accomplishments that have occurred in this field during the last several years that might change approaches of design and increase greatly the information processing potentialities in reaction-diffusion systems.

An attempt was made above to demonstrate that reaction-diffusion systems are capable of effectively implementing image processing operations, labyrinth problems, and recognition capabilities—the most widely-known problems of high computational complexity.

The very remarkable feature of the last several years has been that different research groups have begun to use a reaction-diffusion approach to solve diverse practical problems. Sendi a-Nadal and Colleagues (Sendi a-Nadal et al. 1998) experimentally and theoretically investigated percolation thresholds based on chemical light-sensitive excitable media. Light excitation enables one to create a number of sites of predetermined shape and size. Spreading a planar wave front in this medium gave the opportunity to observe different percolation thresholds. The system investigated (Sendi a-Nadal et al. 1998) is similar to the situation found in experiments of disordered semiconductors. Using similar techniques, Sendi a-Nadal and Colleagues (Sendi a-Nadal et al. 1998b) also studied wave propagation in a medium with disordered excitability.

Yoshikawa and his coworkers (Yoshikawa, Motoike, and Kajiya 1997; Yamaguchi et al. 1998; Motoike and Yoshikawa, 1999) found that unidirectional signal transmission with an excited propagating wave can be generated by a chemical diode—a spatially asymmetric connection between excitable fields separated by a diffusion field. They discovered that such a diode function could be created both in an actual experiment (with a Belousov-Zhabotinsky medium) and in computer simulations. These investigations open the way to design a massively parallel computational medium.

One should emphasize that fundamental experimental accomplishments are the basis of the substantial progress of the last several years, greatly increasing the reliability of experimental data. The decisive step toward experimental implementation of the information processing capabilities inherent in these media had been made by Kuhnert and Colleagues (Kuhnert 1986, 1986b; Kuhnert, Agladze, and Krinsky 1989), who originally suggested the use of light-sensitive reaction-diffusion BelousovZhabotinsky media for information processing.

The reliability of data has improved greatly during the past decade. Two basic achievements are behind this improvement: the advent of continuous-flow unstirred reactors and the use of polymer matrices, in which the reaction-diffusion phenomena can proceed. The use of polymer materials in reaction-diffusion systems as an indispensable component has proved to be a design solution of very great importance.

Many useful ways of using polymer materials for investigating chemical oscillators are known (for details, see Rambidi, Kuular, and Machaeva 1998). Nevertheless, the design of information processing devices based on reaction-diffusion systems faces a number of additional problems: The investigation of information processing operations is based on the visualization of processes occurring in these systems. Therefore a high-quality level of detection of the structures arising in such processes is necessary.

Let us discuss the main potentialities of using polymer materials in reactiondiffusion systems, with a view to their information processing applications (Rambidi, Kuular, and Machaeva 1998).

  1. There are several main techniques that depend strongly on the peculiarities of the input and output of initial data to and from the system and the methods of control. Optical methods have been, until now, the basic tools for the input and output of information to and from reaction-diffusion media and for the control of medium functioning. Projecting an image under investigation—that is, a nonuniform spatial light intensity distribution onto the surface of the medium—causes the formation of a nonuniform spatial distribution in the system components and provokes the beginning of the subsequent system evolution.

    Two main factors determine the adequacy of conversion of an input light picture to a molecular distribution corresponding to this picture. The first of these is the uniformity of the primary light intensity distribution used for the input of data. If the distribution is nonuniform, it is equivalent to an additional nonuniform background that is superimposed on the image under processing. The degree of light uniformity should be rather high because the sensitivity of the medium to changes in light intensity has proved to be significant.

    The second factor is the constancy of the medium layer thickness. If the thickness is nonuniform (figure 4.28), the stages of image evolution do not proceed simultaneously at different points of the image under processing. This effect hampers image processing by reaction-diffusion media.

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    Figure 4.28: Different realizations of light-sensitive polymer based reaction-diffusion media: a thin flat layer of liquid medium (A), a liquid medium in a polymer matrix, for instance in thin flat layer of polyacrylamide gel (B), a system where a catalyst is immobilized on a solid support (C).

  2. Using polymer materials as inert matrices in which the reaction-diffusion proceeds greatly improves the quality of images in the media. A flat two-dimensional layer of a polymer usually contains 80–90 percent water in the polymer framework. This water can be replaced easily by a solution of the reaction-diffusion medium. As a result, this system (polymer plus reagent) seems to be of low sensitivity to mechanical forces (vibrations and so on), hydrodynamic effects, and surface evaporation. Moreover, it proves to be practically insensitive to the inclinations of the system layer with respect to the Earth's vertical—that is, the thickness of the medium layer becomes constant.

  3. Polymer media are very convenient for designing spatially nonuniform versions of reaction-diffusion systems. They enable one to design predetermined spatial gel structures and to determine, as a result, the mode of functioning of the reactiondiffusion system.

    Let us mention only two of the most simple and naive examples. Immobilization of the catalyst in the Belousov-Zhabotinsky reaction onto the surface of a solid carrier transforms the system into a pseudo-two-level system. In this case, the reaction components are in the liquid phase but the reaction itself proceeds at the boundary of the phases.

    Steinbock and coworkers (Steinbock, Kettunen, and Showalter 1996) used a simple two-level system for the implementation of chemical wave logic gates. They plotted a drawing of the gate onto the surface of a membrane placed on the agarose polymer layer. All other components of the Belousov-Zhabotinsky reaction were in the volume of the gel. The wave proceeding in the gel switched the logic states of the device.

  4. A polymer matrix could control the mode of a reaction-diffusion system designed on the basis of this matrix. Kazanskaya and Colleagues (Kazanskaya et al. 1996; Eremeev, Kukhtin, and Kazanskaya 1998) elaborated two different systems of this kind. The first one consisted of polymer membrane containing a photosensitive component—spiropyrane. When the spiropyrane is incorporated into the polymer membrane, its potential changes upon UV irradiation of the membrane surface. The ionophore nonactin was introduced into the membrane to couple the membrane photoresponse with urea hydrolysis catalyzed by urease. The urea hydrolysis proceeded in another polymer matrix combined with a photosensitive membrane.

    The second system was a two-level spatially combined one. It consisted of a thermosensitive polymer matrix saturated by urease. Enzyme activity was a function of temperature near the point of reversible collapse of the gel.

    Further investigations in this field seem to give the opportunity to design complicated systems capable of performing complex logical functions.

  5. Finally, possibilities exist to design chemical nonlinear dynamic systems wherein the polymer is used as one of the components of the chemical process. This could provide an opportunity to create a predetermined structure in the gel matrix at some stages of the dynamic process. This structure of the gel will determine the mode of subsequent processes in the matrix. In some sense, this seems to be the analogue of long-term memory organization.

The above-discussed various design solutions based on polymer materials are currently at different levels of understanding and implementation.

Let us mention that further progress of experimental technique should lie in the basis implementing the above possibilities. Recently, new phenomena were investigated that seem to be quite promising for elaborating more effective information processing devices.

Toth, Gaspar, and Showalter (1994) performed a detailed study of signal transmission through capillary tubes. Possibilities of controlling the shape of the wave front based on light excitations of the reaction-diffusion medium were offered by Sendi a-Nadal and Colleagues (Sendi a-Nadal et al. 1997).

The coupling of chemical oscillators was studied (Miyakawa et al. 1995; Miyakawa and Mizoguchi 1998) in systems formed by immersing cation exchange beads loaded with ferroin in the Belousov-Zhabotinsky reagent. Cation exchange beads of about 500 mm in diameter were used.

Other investigations of sufficient interest should be mentioned:

  • Formation of scroll waves in photosensitive media (Amemiya et al. 1998)

  • Wave propagation along the line of a velocity jump (Steinbock, Zykov, and Muller 1993)

  • Splitting of autowaves in an active medium (Mu uzuri, P rez-Villar, and Markus 1997)

  • Some works concerning interactions of spiral waves (Ruiz-Villarreal et al. 1996; Mu uzuri, P rez-Mu uzuri, and P rez-Villar 1998)

All these examples show that the last several years have been quite successful in further progress of experimental techniques. Some of these studies, moreover, seem to be important for constructing a new generation of information processing devices.

Based on the previous discussion, one should also conclude that multilevel systems will be an important source for further progress in this field. It was stressed above that nonlinear mechanisms and multilevel architecture are two basic features of a complex system with increased behavioral complexity.

The last point that should be considered in discussing future potentialities of the reaction-diffusion paradigm is the information processing nature of reaction-diffusion systems. This point is very important for choosing the fields where this paradigm should be the most effective.

In the late 1980s, Conrad (1989) discussed in detail the analogy and lack of analogy between information features of the brain and that of digital von Neumann computers. In the background of this analysis lies the trade-off principle formulated by Conrad (1985):

"A system cannot at the same time be effectively programmable at the level of structure, amendable to evolution by variation and selection, and computationally efficient" (464).

Proceeding from the trade-off principle, Conrad paid attention just to those differences between the information features of the brain and von Neumann computers that are of fundamental significance (figure 4.29). He concluded that according to these differences, von Neumann computers could not pass the Turing test (Turing 1950)—namely, that the intellect of the brain differs appreciably from the possible degree of von Neumann computer intellect.

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Figure 4.29: Brain [] machine [] reaction-diffusion processor [?] analogies-disanalogies.

Conrad (1989) stressed that information processing devices based on principles of information processing at the molecular level should possess information features extremely similar to the information features of the brain. Therefore it seems reasonable to consider information features of reaction-diffusion systems that can now be designed utilizing contemporary laboratory technology (Rambidi 1994).

Let us choose as such devices a reaction-diffusion system using BelousovZhabotinsky media. Let us consider the basic information features of this device.

First, there is a high degree of organization inherent in molecular media of this type. These media display gradualism (i.e., small changes of active medium composition), which, within definite limits, lead only to small quantitative and not qualitative changes of system dynamics.

Also, Belousov-Zhabotinsky media have other necessary characteristics for displaying adaptive behavior, as according to Ashby (1960). Among these is the nature of the interaction of the system with the environment, feedback organization, and so on. Therefore we can conclude that it could really be possible to create a device that is capable of learning, has multilevel architecture, and has a high degree of behavioral complexity.

It is easy to see that the lack of structural programmability, a high degree of parallelism, mixed continuous and discrete dynamics, and highly developed couplings between elements of the medium are typical in reaction-diffusion means (see figure 4.29). Even simple reaction-diffusion systems display a vertical flow of transmission and processing information. Also, even in a simple system, the following can be determined:

  • The level of macro-micro type transformation of information (in particular, photochemical transformation of a light two-dimensional picture into pseudo-twodimensional distribution of reaction components)

  • Dynamics at the molecular level implementing a definite information process

  • The level of micro-macro information transformation (i.e., physicochemical reading information)

Unlike the digital von Neumann computer, the reaction-diffusion device is not a rigid, structurally predetermined system. Its dynamics depends on the composition and control stimuli variations. It enables implementation of rather effective control of the dynamics.

In general, a detailed comparison of the information features of the brain, the digital von Neumann computer, and reaction-diffusion media leads to the conclusion that there is a sufficiently greater analogy between features of reactiondiffusion media and the brain. From the considerations discussed above, it seems to follow that it is the complicated nonlinear dynamics that determines the information features inherent in reaction-diffusion biomolecular devices. At the same time, the surprising resemblance of features of the brain and simple enough reactiondiffusion systems that determine the general principles of information processing (self-organization, high parallelism, vertical flow of information, etc.) is striking.

The brain is immeasurably richer in its functions than a specialized reactiondiffusion device. The completeness of solving intellectual problems by brain exceeds all that can be reached nowadays by any "man-made" device. Nevertheless, the analogy of information processing features seems to be the evidence that there exists a set of logical operations inherent in reaction-diffusion systems that are optimal and whose mechanisms are close to the analogous mechanisms of the brain.




Molecular Computing
Molecular Computing
ISBN: 0262693313
EAN: 2147483647
Year: 2003
Pages: 94

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