Researchers from the Artificial Intelligence Group (LIA) at the Universidad Politécnica de Madrid’s School of Computing have designed a biomolecular automaton and several genetic circuits with potential future applications in the field of vanguard medicine.
Depending on how it is programmed, the molecular automaton detects DNA or RNA signals in vitro. In the future, though, provided it passes all the experimental tests, it will be able to operate inside the human organism.
The ultimate aim of a molecular automaton is to detect and treat diseases in situ inside a human organism. Fitted inside the organism, the automaton detects anomalies and dispenses the right medicine at the right time. Biomolecular automata are artificial devices built with biomolecules and designed to operate inside a living organism.
These automata are engineered by first drafting a pencil-and-paper design or specification. Then a mathematical model is built describing the equations governing its operation. This is followed by a computer simulation. Finally, the automaton is implemented in a biotechnology laboratory. The whole process will be repeated cyclically until the automaton has the desired features and functionality.
The design and application of programmable molecular automata to the diagnosis and in vivo treatment of diseases (also known as intelligent drug) is a recent and promising application of DNA computing to biomedicine, which was initiated by Prof. Yaakov Benenson in 2004.
The new biomolecular automaton designed and modelled at the UPM’s School of Computing has been sent to the Technische Universität München’s nanobiotechology laboratory for implementation and, if it works, will be applied to medical research.
The LIA has also designed several circuits or synthetic biological oscillators, whose job is to synchronize the activity of biomolecular automata in a living system.
One of the synthetic biomolecular circuit designs developed by this group is to be presented at the 3rd International Workshop on Practical Applications of Computational Biology & Bioinformatics (IWPACBB’09) to be held in Salamanca (Spain) this week.
The synthetic genetic circuit to be presented at Salamanca outputs a biological signal. The signal concentration alternates at regular time intervals and can be used as a clock signal for synchronizing biological processes. The clock signal frequency of this oscillating circuit can be modified (faster or slower clock), and it will act on a biological circuit in the same way as the clock signal in digital computers.
This design will also be implemented at the Technische Universität München and, if it works properly, will be donated to the Registry of Standard Biological Parts, the open source genetic circuits design database maintained by the Biobricks Foundation, associated with MIT.
This circuit or genetic oscillator is to be used as a module for synchronizing the activity of other modules of a more complex genetic circuit or as a synchronization signal controlling the activity and the operating rate of a set of biomolecular automata. These oscillating circuits are like traffic lights deployed inside a cell or a bacteria that control and regulate the operation of the other circuits or biomolecular automata.
The aim of this project, which kicked off in 2006 and is to wind up at the end of 2009, is to advance natural computing and systems biology using a cell-inspired distributed computing model (called P system or membrane computing), as well as to develop synthetic biology by designing new circuits and biomolecular automata.
As a branch of science, natural computing has two goals: understand the computational processes taking place in nature (particularly, biology) and develop computational models inspired by nature. Systems biology pursues the challenge of developing robust and precise mathematical models whose application can describe, understand and make predictions on complex biological systems and processes. The budding discipline of synthetic biology aims to design and build new devices and artificial biological organisms, as well as redesign and reprogram natural biological systems.