My research interests lie in the field of molecular recognition, and in particular the development of artificial recognition elements. Towards this end I use a technique known as Molecular Imprinting.
Molecularly Imprinted Polymers (MIP) are a simple elegant biomimetic technology where recognition sites, analogous to the binding sites of antibodies, enzymes and receptors are created in polymeric materials containing complementary functionality to a target molecule. After preparation cavities that are complementary to the shape and chemical profile of the target are formed allowing specific recognition and rebinding. MIPs represent a generic, versatile, scalable and cost-effective approach to the creation of synthetic molecular receptors; and are rapidly becoming commercially relevant. My work is focused on:
1: MIPs for trace capture and analysis. Preparation of Solid Phase Extraction (SPE) materials for biomarkers, toxins, pollutants, explosives and pharmaceuticals analysis. This is a traditional imprinting area where polymers are used as targeted clean-up for further analytical study.
2: Hybrid imprinting using biological materials as monomers The development of imprinted nanoparticles that are hybrids between aptamers (short chains of single strand DNA that have molecular recognition properties) and MIPs. These apta-MIPs maintained the best properties of both classes of materials. They demonstrated high affinity and specificity, towards their targets. In addition they addressed the stability issues associated with aptamers. This work is in collaboration with Dr Jon Watts (UMass, RTI Institute, USA).
3: Macromolecule Imprinting Investigating selective rebinding of proteins for biological sample clean-up. I am also interested in developing materials specific for different isoforms of the same protein. These will be used in the development of sensors for early analysis of protein conformational diseases such as Alzheimer's. The same imprints are under study to guide protein folding.
4: Biosensor design Using MIPs and other recognition elements to generate next-generation biosensor platforms.