The SSIP approach to protein-ligand complex interactions

Lead Research Organisation: University of Cambridge
Department Name: Chemistry


Year 1: Generic training activities for all first-year student members of the CDT.

Year 2-4: The field of drug discovery faces a dichotomy. It is possible to screen high volume of small molecules but algorithms that do are empirically parametrised and quantify non-covalent interactions. To obtain high quality detail takes a substantial amount of time, skill, and computing power. Both high volume and high quality algorithms, however, use an energy predictor and an optimisation tool that leads the search to equilibrium. We will develop a Surface Site Interaction Point model that uses DFT-calculated detail in quick quantification of interactions. It reliably describes the interaction patterns present between molecules. It reliably predicts solvation energies, and in considering protein-ligand complexes, it can describe non-covalent interactions within a conformation without a need for explicit solvent treatment. Here we show such an approach gives good estimates of binding affinities using a common dataset - CASF-2016. We can predict and quantify interactions present in a complex, therefore providing a path to systematic drug candidate optimisation. If coupled with an optimisation algorithm, this new approach could form a tool for screening ligands, thus yielding a unified approach to drug design that is both swift and accurate.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S024220/1 31/05/2019 30/11/2027
2468566 Studentship EP/S024220/1 30/09/2020 29/09/2024 Katarzyna Zator