Quantum mechanics and cellular information processing: the self-assembly paradigm.
Biological cells have greater information processing efficiency than the programmable computers used to model them. In part this is due to the larger number of interactions that can contribute to function. General arguments suggest that systems in which quantum features play a prominent role are more powerful than classical physical-dynamical analogs. A hypothetical model, involving macromolecular self-assembly, is used to illustrate how the parallelism inherent in the quantum mechanical wave function could play a role in cellular pattern processing. Signals impinging on the external membrane of the cell trigger the release of specifically shaped macromolecules. These aggregate into a mosaic shape features that reflect different groupings of the signal input patterns. The shape features are in turn read out and connected to effector actions by adaptor molecules. The self-assembly model fits into a more general hierarchical scheme of biological information processing in which macroscopic signals are transduced to mesoscopic and then microphysical representations, processed largely at the microphysical level, and then amplified for macroscopic action. The physical dynamics are controlled by proteins and other macromolecules that are molded through the evolutionary process of variation and selection. The organizational requirements for evolutionary moldability and for efficient information processing function are completely consistent. They include high dimensionality, multiplicity of weak interactions, and hierarchical-compartmental structure.
Conrad
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Department of Computer Science, Wayne State University, Detroit, Michigan 48202.
D005075:Biological Evolution; D003198:Computer Simulation; D008954:Models, Biological; D010363:Pattern Recognition, Automated; D011789:Quantum Theory; D012641:Selection, Genetic; D013329:Structure-Activity Relationship