Systems Chemistry: Logic Gates, Arithmetic Units, and Network Motifs in Small Networks

Abstract

A mixture of molecules can be regarded as a network if all the molecular components participate in some kind of interaction with other molecules--either physical or functional interactions. Template-assisted ligation reactions that direct replication processes can serve as the functional elements that connect two members of a chemical network. In such a process, the template does not necessarily catalyze its own formation, but rather the formation of another molecule, which in turn can operate as a template for reactions within the network medium. It was postulated that even networks made up of small numbers of molecules possess a wealth of molecular information sufficient to perform rather complex behavior. To probe this assumption, we have constructed virtual arrays consisting of three replicating molecules, in which dimer templates are capable of catalyzing reactants to form additional templates. By using realistic parameters from peptides or DNA replication experiments, we simulate the construction of various functional motifs within the networks. Specifically, we have designed and implemented each of the three-element Boolean logic gates, and show how these networks are assembled from four basic "building blocks". We also show how the catalytic pathways can be wired together to perform more complex arithmetic units and network motifs, such as the half adder and half subtractor computational modules, and the coherent feed-forward loop network motifs under different sets of parameters. As in previous studies of chemical networks, some of the systems described display behavior that would be difficult to predict without the numerical simulations. Furthermore, the simulations reveal trends and characteristics that should be useful as "recipes" for future design of experimental functional motifs and for potential integration into modular circuits and molecular computation devices.

Control of Noise in Chemical and Biochemical Information Processing

“…[18][19][20] Reported results for networks [1][2][3][4][18][19][20] of (bio)chemical information processing units have included systems performing elements of basic arithmetic operations, [21][22] multifunctional molecules, [23][24][25] DNAbased gates and circuits, [26,27] and enzyme-catalyzed reactions realizing concatenated gates. [19,20,28,29] Here we introduce, by illustrative model examples, concepts in noise reduction and control for scalability in biochemical computing.…”

Deconvolution of a multi-component interaction network using systems chemistry

“…The success of systems biology [1,[7][8][9][10][11] in the reconstruction of complex functional systems based on a fundamental understanding of the behavior of a series of biological components has served as a stimulus for chemists to begin to develop systems chemistry with the goal of creating functional systems by combining the behaviors of well characterized chemical building blocks [12][13][14]. For example, the Ghadiri group has explored the behavior of complex systems comprising peptides, enzyme, and/or DNA toward the construction of systems that display self-replication, Boolean logic, and that even are subject to evolutionary pressures [15][16][17][18][19][20].…”

Fluorescent logic systems for sensing and molecular computation: structure–activity relationships in edge-detection

“…The rustle of the undergrowth alerts him to an 35 approaching animal. Will it be food or will he be food for it?…”

“…So we have accidental overlap with the writing wavelength causing serious competitive absorption at the concentrations employed in our study. The photoacid generator 1's maximum ε is only 1.9x10 4 M -1 cm -1 at 35 235 nm. 37 The non-emissive appearance of the irradiated region would suggest oxidative photodecomposition of 7 following direct excitation and subsequent PET to 1.…”

“…However, the most visual aspect of the photograph at 32 min 35 writing is that an orange fluorescence decorates the original edges of the square object. Edge detection in blue-green, in green and in orange were previously shown with sensors 5, 6 and 3 respectively.…”