In situ generation of RNA complexes for synthetic molecular strand displacement circuits in autonomous systems

Synthetic molecular circuits implementing DNA or RNA strand-displacement reactions can be used to build complex systems such as molecular computers and feedback control systems. Despite recent advances, application of nucleic acid-based circuits in vivo remains challenging due to a lack of efficient methods to produce their essential components – multi-stranded complexes known as “gates” – in situ, i.e. in living cells or other autonomous systems. Here, we propose the use of naturally occurring self-cleaving ribozymes to cut a single-stranded RNA transcript into a gate complex of shorter strands, thereby opening new possibilities for the autonomous and continuous production of RNA strands in a stoichiometrically and structurally controlled way.

A Molecular Computing Approach to Solving Optimization Problems via Programmable Microdroplet Arrays

The search for novel forms of computing that show advantages as alternatives to the dominant von-Neuman model-based computing is important as it will enable different classes of problems to be solved. By using droplets and room-temperature processes, molecular computing is a promising research direction with potential biocompatibility and cost advantages. In this work, we present a new approach for computation using a network of chemical reactions taking place within an array of spatially localized droplets whose contents represent bits of information. Combinatorial optimization problems are mapped to an Ising Hamiltonian and encoded in the form of intra- and inter- droplet interactions. The problem is solved by initiating the chemical reactions within the droplets and allowing the system to reach a steady-state; in effect, we are annealing the effective spin system to its ground state. We propose two implementations of the idea, which we ordered in terms of increasing complexity. First, we introduce a hybrid classical-molecular computer where droplet properties are measured and fed into a classical computer. Based on the given optimization problem, the classical computer then directs further reactions via optical or electrochemical inputs. A simulated model of the hybrid classical-molecular computer is used to solve boolean satisfiability and a lattice protein model. Second, we propose architectures for purely molecular computers that rely on pre-programmed nearest-neighbour inter-droplet communication via energy or mass transfer.

A Molecular Computing Approach to Solving Optimization Problems via Programmable Microdroplet Arrays

The search for novel forms of computing that show advantages as alternatives to the dominant von-Neuman model-based computing is important as it will enable different classes of problems to be solved. By using droplets and room-temperature processes, molecular computing is a promising research direction with potential biocompatibility and cost advantages. In this work, we present a new approach for computation using a network of chemical reactions taking place within an array of spatially localized droplets whose contents represent bits of information. Combinatorial optimization problems are mapped to an Ising Hamiltonian and encoded in the form of intra- and inter- droplet interactions. The problem is solved by initiating the chemical reactions within the droplets and allowing the system to reach a steady-state; in effect, we are annealing the effective spin system to its ground state. We propose two implementations of the idea, which we ordered in terms of increasing complexity. First, we introduce a hybrid classical-molecular computer where droplet properties are measured and fed into a classical computer. Based on the given optimization problem, the classical computer then directs further reactions via optical or electrochemical inputs. A simulated model of the hybrid classical-molecular computer is used to solve boolean satisfiability and a lattice protein model. Second, we propose architectures for purely molecular computers that rely on pre-programmed nearest-neighbour inter-droplet communication via energy or mass transfer.

Molecular Computing and Bioinformatics

Molecular computing and bioinformatics are two important interdisciplinary sciences that study molecules and computers. Molecular computing is a branch of computing that uses DNA, biochemistry, and molecular biology hardware, instead of traditional silicon-based computer technologies. Research and development in this area concerns theory, experiments, and applications of molecular computing. The core advantage of molecular computing is its potential to pack vastly more circuitry onto a microchip than silicon will ever be capable of—and to do it cheaply. Molecules are only a few nanometers in size, making it possible to manufacture chips that contain billions—even trillions—of switches and components. To develop molecular computers, computer scientists must draw on expertise in subjects not usually associated with their field, including organic chemistry, molecular biology, bioengineering, and smart materials. Bioinformatics works on the contrary; bioinformatics researchers develop novel algorithms or software tools for computing or predicting the molecular structure or function. Molecular computing and bioinformatics pay attention to the same object, and have close relationships, but work toward different orientations.

Nucleic Acid Computing and its Potential to Transform Silicon-Based Technology

Molecular computers have existed on our planet for more than 3.5 billion years. Molecular computing devices, composed of biological substances such as nucleic acids, are responsible for the logical processing of a variety of inputs, creating viable outputs that are key components of the cellular machinery of all living organisms. We have begun to adopt some of the structural and functional knowledge of the cellular apparatus in order to fabricate nucleic-acid-based molecular computers in vitro and in vivo. Nucleic acid computing is directly dependent on advances in DNA and RNA nanotechnology. The field is still emerging and a number of challenges persist. Perhaps the most salient among these is how to translate a variety of nucleic-acid-based logic gates, developed by numerous research laboratories, into the realm of silicon-based computing. This mini-review provides some basic information on the advances in nucleic-acid-based computing and its potential to serve as an alternative that can revolutionize silicon-based technology.

Recent Advances in Molecular Magnetic Materials

This review describes advances made in three areas of molecular magnetic materials of the types A: extended frameworks (coordination polymers) showing long-range magnetic order, B: spin-coupled clusters with emphasis on single molecule magnets and (n × n) grid species, C: polynuclear spin-switching (spin crossover) compounds of FeII with emphasis on dinuclear compounds and one-dimensional (1D) and three-dimensional (3D) (framework) materials, including porous ‘hybrid’ systems. The work of the author and his group is largely used to provide examples, together with results from other groups and collaborators that are included for comparison and completeness. Supramolecular aspects such as cluster–cluster and chain–chain interactions are discussed where relevant. A brief discussion is also given of the recent studies, carried out elsewhere, dealing with aspects of spintronics and the possible future relevance to molecular computers (type B materials) and with memory and other device possibilities (type C materials)