Information processing in molecular systems

Nonequilibrium Self-Organization of Lipids into Hierarchically Ordered and Compositionally Graded Cylindrical Smectics

When a dry mass of certain amphiphiles encounters water, a spectacular interfacial instability ensues: It gives rise to the formation of ensembles of fingerlike tubular protrusions called myelin figures─tens of micrometers wide and tens to hundreds of micrometers long─representing a novel class of nonequilibrium higher-order self-organization. Here, we report that when phase-separating mixtures of unsaturated lipid, cholesterol, and sphingomyelin are hydrated, the resulting myelins break symmetry and couple their compositional degrees of freedom with the extended myelinic morphology: They produce complementary, interlamellar radial gradients of concentrations of cholesterol (and sphingomyelin) and unsaturated lipid, which stands in stark contrast to interlamellar, lateral phase separation in equilibrated morphologies. Furthermore, the corresponding gradients of molecule-specific chemistries (i.e., cholesterol extraction by methyl-β-cyclodextrin and GM₁ binding by cholera toxin) produce unusual morphologies comprising compositionally graded vesicles and buckled tubes. We propose that kinetic differences in the information processing of hydration characteristics of individual molecules while expending energy dictate this novel behavior of lipid mixtures undergoing hydration.

How Chemistry Computes: Language Recognition by Non-Biochemical Chemical Automata. From Finite Automata to Turing Machines

Every problem in computing can be cast as decision problems of whether strings are in a language or not. Computations and language recognition are carried out by three classes of automata, the most complex of which is the Turing machine. Living systems compute using biochemistry; in the artificial, computation today is mostly electronic. Thinking of chemical reactions as molecular recognition machines, and without using biochemistry, we realize one automaton in each class by means of one-pot, table top chemical reactors: from the simplest, Finite automata, to the most complex, Turing machines. Language acceptance/rejection criteria by automata can be formulated using energy considerations. Our Turing machine uses the Belousov-Zhabotinsky chemical reaction and checks the same symbol in an Avogadro′s number of processors. Our findings have implications for chemical and general computing, artificial intelligence, bioengineering, the study of the origin and presence of life on other planets, and for artificial biology.

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Computations are language recognition events carried out by “computing automata”

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Chemical reactions are molecular recognition events equivalent to automata

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Words in a language can be represented by sequences of chemical reactants

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Inorganic reactions like automata, including Turing machines, recognize languages

Molecular associative memory

An example of a kinetic system with address-bearing molecules and directed interactions is investigated. We show that by introducing exchange between Ising spins via the address-bearing messengers, the Hopfield model of associative memory can be made local.

Evolution and gradualness

Evolutionary systems are commonly considered to have fundamental properties: (1) elements (or organisms) in the system reproduce with mutation and (2) only the fit elements survive. I propose that evolutionary systems have a third property - the property of gradualness. A system has gradualness, if, and only if, small changes in an element usually lead to small changes in that element's fitness. I have formalized a framework from which attempts to design evolutionary systems might proceed. Of particular importance are the criteria, based on the notion of perpetuation, which a system's behavior must satisfy in order to be considered evolutionary. By my standards, no computer programs have been designed that manifest meaningful evolutionary behavior.