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Details of Grant 

EPSRC Reference: EP/V046594/1
Title: Directed Molecular Recognition through Next-Generation Hybrid Molecular Imprinting
Principal Investigator: Turner, Professor NW
Other Investigators:
Researcher Co-Investigators:
Project Partners:
MIP Diagnostics Limited
Department: School of Pharmacy
Organisation: De Montfort University
Scheme: Standard Research
Starts: 01 October 2021 Ends: 28 February 2023 Value (£): 270,150
EPSRC Research Topic Classifications:
Biophysics Chemical Biology
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
21 Apr 2021 EPSRC Physical Sciences 21 and 22 April 2021 Announced
Summary on Grant Application Form
The increasing demand for highly effective molecular recognition for sensing and separations has led researchers to search for synthetic substitutes for enzymes and antibodies with emphasis on materials with potential to outperform their biological counterparts in terms of cost, performance, stability and flexibility.

Molecularly Imprinted Polymers (MIPs) are elegant biomimetics that incorporate binding sites bearing steric and chemical functionality complementary to a given target. They represent a generic, versatile, scalable, cost-effective approach to the creation of synthetic molecular receptors and have uses in separation sciences, purification, sensors and catalysis.

In "classical" molecular imprinting, small functional monomers are used to create the binding sites. While this method has proven generally effective, a relatively high level of heterogeneity in rebinding is still observed which lowers the average binding constant and leads to much-reduced selectivity. This "Achilles Heel" has prevented MIPs from fulfilling their potential, and has led to only their limited application in niche areas. A solution to the heterogeneity problem would unleash the transformational potential of MIPs within the multi-billion-dollar diagnostic and analytical markets.

This heterogeneity arises because of the nature of the imprinting process, where functionality is introduced to the target in a random fashion, leaving no scope for the correction of errors that arise during the subsequent formation of the binding pocket in the polymeric matrix. We will address these issues by developing a novel two-step process towards the formation of imprinted polymeric nanoparticles of exceptionally high affinity and selectivity.

It will exploit a method developed by Fulton that introduces error-correction into the templating process, and a separate method developed by Turner to then fix the binding site within a rigid polymeric nanoparticle "scaffold". This hybridisation will deliver optimized binding sites "locked" into a more rigid structure - creating new synthetic biomimetics with reduced heterogeneity, while incorporating biocompatibility through component selection. These hybrid MIPs can truly challenge and replace their biological counterparts - creating significant impact in the field of molecular recognition and smart materials.

Two targets have been selected to drive the development of these chemistries. These differ in size and application: a protein and a bioactive (antibiotic) drug, but both targets have significant commercial potential, in clinical and environmental settings. Monitoring of antibiotics is key for understanding required effective dosage, but also for studying leakage into the environment from illegal use or overuse, which leads to numerous other serious issues such as bacterial resistance. The protein target offers a demonstration of the MIP nanoparticle ability to disrupt ligand-receptor binding, where the MIP itself can act with inhibitory "drug-like" properties. Through these models we aim to demonstrate the validity and potential of the proposed novel MIP systems.

The project will use facilities at De Montfort University and Newcastle University to develop the new approach. With an experienced project team this interdisciplinary proposal, which covers organic, polymer and analytical chemistry, will take a new approach to MIP synthesis, building on existing proof-of-concept ideas, and develop them further, translating the novel synthetic processes described here into viable options for artificial molecular recognition which can be exploited in several ways. Here we will develop the synthetic methods to be scalable through clear step processes, with automation in mind.

MIP Diagnostics are a UK company based in Bedford who will support the project by their detailed knowledge of MIP design, implementation, and application, with sight towards commercialisation of the technology.
Key Findings
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