Abstract: In this talk I will present a memory system based on an artificial chemistry. This is relevant as a 'proof of concept' for metabolism based Origin of Life theories, and in the field of biological and chemical computing. Each memory unit can be switched between three alternative active states. A unit maintains itself in a particular state using an autocatalytic reaction process. Switching between states occurs when an external stimulus triggers the autocatalytic process for the new state, along with an associated process that inhibits autocatalytic activity for the old state. I will show artificial molecular species with structures that support the autocatalytic and inhibiting processes. I will also present results from the SimSoup artificial chemistry simulator showing the operation of a 5-unit memory system with 243 alternative states (equivalent to just under 8 bits of memory). The design supports systems with more units, but computational requirements to run the simulator increase substantially. I will conclude the talk with a short review of some alternative network architectures for chemical memory and inheritance.
Abstract: A memory system based on an artificial chemistry is presented. This is relevant for metabolism based Origin of Life theories, and in the field of biological and chemical computing. Each memory unit can be switched between three alternative active states. A unit maintains itself in a particular state using an autocatalytic reaction process. Switching between states occurs when an external stimulus triggers the autocatalytic process for the new state, along with an associated process that inhibits autocatalytic activity for the old state. Artificial molecular species with structures designed to support the autocatalytic and inhibiting processes are presented. The SimSoup artificial chemistry simulator is used to show that the structures do indeed produce the memory system behaviour. With the advent of engineering at the molecular level, it may be possible to transfer the concepts from an in silico environment to a chemical environment.
Background and Motivation: A key challenge for BioChemIT is the development of evolvable systems. This requires the implementation of a mechanism for inheritance using components that can be readily constructed and manipulated. Contemporary life-forms use RNA and DNA and associated mechanisms. Origin Of Life research suggests that these mechanisms are too complex to be plausible in a prebiotic environment. The SimSoup project is seeking a simpler inheritance mechanism based on chemical networks. This search is relevant from a BioChemIT perspective, with its need for mechanisms that are sufficiently simple to be implementable. This paper summarises in silico work on an inheritance mechanism using molecular structures designed to produce autocatalytic reaction networks. The motivation is to highlight the potential of this approach for a practical evolutionary mechanism in a BioChemIT context. The paper concludes by identifying key requirements for a BioChemIT implementation of such a mechanism.
Abstract: Theories of the Origin of Life can be categorised as ‘template replication first’ and ‘metabolism first’. A key question for metabolism first theories is whether metabolic systems can support open-ended evolution; this is related to the number of possible persistent states of such a system. Earlier work has demonstrated that artificial chemical systems can have memory; an essential requirement for inheritance. The current paper extends this, taking a ‘proof of concept’ approach to the question of the number of persistent states. It shows an artificial chemical network forming a ‘memory bank’ with many possible states. It also makes the link between chemical network structure and molecular structure, and provides a design for a set of artificial molecular species for the memory bank network. Preliminary simulation results from the SimSoup artificial chemistry simulator are included, confirming the operation of an initial set of ‘memory units’. The work supports the view that open-ended evolution can begin without requiring highly complex template molecules.
Abstract: Origin of Life theories are in two main categories: ‘template replication first’ and ‘metabolism first’. A network oriented viewpoint is presented, under which properties of metabolic networks played a key role in the origin of the first evolving systems. A mechanism for memory in chemical networks is illustrated. The simplicity of `network memory', especially in comparison with template mechanisms, suggests its plausibility as a prebiotic phenomenon and as a fruitful area for Origin of Life research.
Abstract: Network dynamics may have played a key role in the Origin of Life. 'Smart' molecules such as template replicators and enzymes may not have been necessary in the first evolving entities. Instead, a process of natural selection between chemical networks operating in different organisms may have been the key evolutionary mechanism. This paper shows such a process using the SimSoup artificial chemistry simulation. The context and conceptual background for SimSoup is first outlined. The model is then described, and differences with other models are highlighted. SimSoup has network elements that correspond directly to the unimolecular and bimolecular elementary reaction schemes of physical chemistry. These network elements can be combined in very general ways to produce 'compound interactions' which can be catalytic. The model includes mass conservation, reaction rates based on considerations of energy and thermodynamics, and cycle detection. A run of the model is presented showing an evolutionary process in which a metabolic network is modified at periodic intervals, and the modification is accepted or discarded according to whether or not it results in higher metabolic activity. The network includes a large number of cyclic flows. It evolves through a series of persistent states, each of which can be regarded as a different 'species'.
Abstract: The mechanism for evolution in the first lifeforms is a key question that must be addressed by any explanation of the Origin of Life. The SimSoup artificial chemistry model is described, and it is shown how catalytic reactions can be represented as 'compound interactions'. A possible mechanism for inheritance in metabolic networks is outlined using graphical notation developed for SimSoup. Preliminary results from computer simulations are presented; it is demonstrated that a SimSoup network has multiple persistent states and that transitions between these states can occur as a result of perturbations or random fluctuations. It is argued that this may have relevance to understanding the mechanism of evolution in early lifeforms.
The presentation provides an outline of and background to the problem of the Origin Of Life, and presents a case for adopting the view that life had a metabolic origin. It includes a simple example of a metabolism based inheritance mechanism. This is illustrated using the SimSoup artificial chemistry simulator.