Project REINFORMATION

Project REINFORMATION

Engineering Ligand-Receptor Interactions for Molecular Communications

Funded by Marie Skłodowska-Curie Actions | Individual Fellowships
Duration: 2021 – 2023
Amount: 145K Euro

Molecular Communications (MC) is the nature’s way of networking at nanoscale, observed in almost all biological systems, including bacterial populations and nervous system. MC has been widely studied to enable the networks of artificial nanoscale devices promoting new high-impact applications such as intrabody continuous health monitoring with mobile nanosensor networks. At the core of the natural MC systems lies the ligand-receptor (LR) binding interactions, which provide the selectivity of information transfer. Likewise, LR interactions are essential for artificial MC systems to have a selective and reliable channel/receiver interface in the form of a biorecognition layer consisting of ligand receptors. Recent studies have revealed the dramatic impact of LR interactions on the overall MC performance in terms of channel bandwidth, molecular interference, receiver sensitivity and dynamic range, posing a multi-objective optimisation problem. 

The aim of REINFORMATION is to understand, optimise and engineer the LR interactions for high data-rate and reliable MC systems. To this end, the project will first deliver a realistic theoretical modelling and optimisation framework for MC accompanied by a microfluidic experimental test and validation platform with graphene aptasensor-based MC receivers. The framework will provide the first experimentally validated micro/nanoscale MC models, and enable the optimisation of binding affinity and kinetic rates of LR interactions from the MC perspective. The optimisation results will guide the rational design of new aptamer receptors for target information-carrying proteins, which will then be implemented on the experimental platform. The project will finally provide novel MC modulation and detection techniques, exploiting the LR interactions for high data-rate and reliable MC. Combining expertise in MC, nanotechnology, and computational biology, the project will remove a major barrier to the development of practical MC applications.