Molecular imprinting involves making a binding pocket in a polymer which is chemically and shape specific for the target compound. These "smart plastics" offer robustness compared to biological molecular recognition elements such as antibodies and enzymes. They also have the ability to work in extreme environmental conditions. However, they can sometimes lack the necessary specificity/affinity. Aptamers are small pieces of DNA/RNA that have the ability to target proteins and small molecules and bind to them with high specificity and affinity. They are not toxic and are attractive alternatives to antibodies. They have been used primarily in research due to their susceptibility to enzymatic and chemical degradation, though this is slowly changing and they are becoming commercially relevant. The global aptamers market is projected to reach $2.4 billion by 2020, up from $1.1 billion in 2015. A 12-month proof-of-concept study, supported by the EPSRC and led by the PI (a molecular imprinting specialist), created novel hybrid materials made by incorporating aptamers into molecularly imprinted polymers (MIPs). In simple terms, the aptamer structure is modified to allow it to be directly incorporated into a polymer, so it will hold its shape while being protected from environmental conditions. Novel, high affinity and stable materials were created. These "aptaMIPs" demonstrated exceptional molecular recognition and offer significant improvements on both MIPs and aptamers in terms of stability, and specific target recognition, effectively maintaining the best properties of both classes of materials. This proposal seeks to explore the potential of aptaMIPs through a two year study into the core chemistry used to create these novel materials. We will build on the results of the pilot study and create useful, effective materials with high commercial potential. The research in this proposal will focus on: (i) Identifying the right linker chemistry; (ii) Developing polymerisable modifications for all four bases; (iii) Identifying how many linkers are needed; (iv) Identifying the best position for these linkers. An in-depth study on these four points will enable a full understanding of the key chemistry of how the aptamer incorporates itself into the polymer and, through this, allow us to understand what makes a good aptaMIP and why. Alongside these the synthetic strategies used will be analysed to ensure the creation of these hybrids is simple and effective. Two targets have been selected to study these chemistries. These differ in size and application: a protein and a bioactive drug, but both targets have significant commercial potential. Through these model systems we aim to demonstrate the validity and potential of aptaMIP materials. Alongside the PI, two project partners form the research team: The Watts group were collaborators on the pilot study and are based at the University of Massachusetts RNA Therapeutics Institute (a world leading school in novel aptamer synthesis). They will support the proposal through access to state-of-the-art synthesis equipment, combined with know-how in oligomer synthesis and application. Aptamer Group are a commercial aptamer development company based in York. Their expertise will benefit the project by providing the known oligomer sequences which will act as the basis for our studies and access to specialised instrumentation. The impact of the project will be supported by their detailed knowledge of the aptamer field and commercial outlook. The experience of the whole team will allow this interdisciplinary proposal, covering the fields of polymer, nucleic acid, protein and analytical chemistries to succeed. We will take aptaMIPs from the existing proof-of-concept stage and develop them, and their synthetic process, into viable competitors in artificial molecular recognition, ready for application in systems where their functionality can be exploited.

A central issue in current robotics is how to scale up to more complex cognitive abilities, such as context dependent learning and prediction. Although insects are often viewed as simple reflexive systems, they are in fact more competent than any existing autonomous robots. They are capable of learning, integration of multisensory cues, real-world navigation, and flexible behavioural choice. As they obtain such competences with relatively small brains, understanding these mechanisms should lead to efficient robot applications. Within biology, there has recently been great interest and substantial advance in understanding the insect brain. So far, modelling of these systems has lagged behind, but it is essential for many reasons. By building models of the insect brain we can evaluate precisely expressed hypotheses about its function, and test which elements are crucial for complex behaviour. Moreover by implementing these hypotheses in hardware on robots we can understand the systems in real behavioural contexts. Thus there is a real opportunity to contribute to biological knowledge at the same time as developing systems that have useful application as robot controllers. Our intention in this project is to develop and evaluate models of learning in insect brains, using a combination of biological experiments, computational modelling, and hardware implementations. In particular we want to examine the neural mechanisms that support forms of learning more complex than simple association. These include context dependence, generalisation, and expectation-based expression of responses. Insight into these capabilities requires closer attention to the details of the mechanisms in the insect. For example, it may be important to understand the different stages and time-scales of learning and how these are supported by different biochemical processes. We can exploit an ideal combination of circumstances to make substantial advances in this area. The PI (Webb) has extensive experience in building robot models of insect behaviour, including implementing sensory and neural processing mechanisms in hardware. Along with the researcher-CI (Wessnitzer) she has developed initial models of the relevant insect brain mechanisms, and has strong connections to the leading biologists working in this area. One of these is the CI (Armstrong) who is using advanced genetic techniques to determine the roles of different structures and signalling pathways in the insect brain. Thus we intend to develop a tightly linked paradigm in which: - behavioural experiments suggested by the models provide data for model evaluation; - hardware implementation of the models provides real world evaluation and motivates abstraction; - abstracted models suggest key functional roles that can be tested using genetic manipulations on the insects. The outcome will be both significantly improved understanding of insect brains and a substantial step towards cognitive controllers in robots.