Modelling protein covalent modifications with molecular simulation and machine learning

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This project will focus on developing and validating FEP methodologies to model the effect of protein structure modifications on molecular recognition mechanisms. Efforts will focus on biologics, peptidomimetic ligands, and covalent ligands for which robust simulation protocols are currently lacking. These classes of ligands present challenges for conventional FEP approaches tailored for small molecules because the ligands are often larger, more flexible, and can covalently bind to their target proteins. To address these issues this research will couple state of the art FEP simulation methodologies available in open-source software with advances in machine learning of potential energy functions to enable accurate modelling of binding energetics. The overall aim is to deliver a suite of protein FEP protocols sufficiently rapid and accurate to enable routine use in industrial R&D. This is an exciting opportunity to develop next-generation computer-aided drug design software and methodologies. Upon completion of the studentship, the successful applicant will have gained strong technical expertise in molecular modelling and worked closely with the life sciences softtware industry sector.