Fragment based drug discovery (FBDD) has established itself as a powerful tool for developing probe and drug candidates by rationally elaborating small chemical fragment hits into larger, optimised lead compounds. The use of X-ray crystallography technologies, such as XChem, as a medium-throughput screening tool for FBDD results in a wealth of structural data on low molecular weight molecules in complex with a protein target. Interpreting this data and distilling it into prioritised suggestions for the elaboration of fragment hits into leads with increased potency and selectivity for the target protein is currently a significant challenge to using this technique. Thus, computational methods to address this problem are in high demand. Introduced in 2016 by Radoux et al. based upon the CSD, fragment hotspot mapping highlights specific interactions a protein makes with a bound fragment. The highest scoring interactions predicted are often those that drive binding of the initial fragment; moderately scoring areas correspond to areas of the binding site into which initial fragment hits can be elaborated. Since crystallographic FBDD campaigns result in multiple structures of the same protein, often with evidence of intrinsic protein flexibility, we combine fragment hotspot maps calculated for each protein/fragment structure into an "ensemble map" for the protein target. Comparing ensemble maps of a target and a related off-target protein from the same protein family can then inform the prioritisation and onward elaboration of fragment hits into lead compounds with a tailored selectivity profile within a target’s protein family. A set of diagnostics for assessing the quality of the method’s predictions has been developed, based on ensembles of apo, fragment-bound, and selective inhibitor bound structures of proteins in two well-researched families: protein kinases and bromodomains.

What fragment hit to follow and how? Using hotspots to prioritise chemistry resources

2019 Fall National Meeting

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