The development of quantum computing-based biomolecular recognition methods for use by researchers at all stages of the translational pathway

The work plan will involve iteration between experimental (UCL) and computational (Evotec, UCL) elements
of the project throughout each of the years of study. Four different FMO applications will be pursued during
the proposed project:
Year 1: FMO-ESPC (electrostatic potential complementarity) - The role of electrostatic interactions is
vital for biomolecular recognition. Integration between FMO and ESPC (FMO-ESPC) will enable the
accurate calculation of the electrostatic potential complementarity (ESPC) between a ligand and the protein
to identify key interaction points critical for SBDD.
Year 2: FMO-PPI (Protein-protein interactions) - Protein-protein interactions (PPIs) are essential for
protein functions. More than 645,000 disease-relevant PPIs have been reported in the human interactome
however only 2% of these drug targets have been addressed with PPI modulators. We will integrate FMO
and PPI (FMO-PPI) to identify residues that are critical for protein-protein binding (hotspots) thus facilitating
structure-based drug design of PPI modulators (SBDD-PPI).
Year 3: FMO-Residence Time - We have developed an accurate means of calculating drug residence time
using steered molecular dynamics. We will integrate Fragment Molecular Orbital (SMD/FMO) computational
modelling for G protein-coupled receptors in a way that can be automated and scaled for use on high-end
computing systems.
Year 4: Development of an online FMO Workflow for use by biomedical researchers