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

点击翻译按钮获取中文摘要

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