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Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins.

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Curran, Peter R 
Radoux, Chris J 
von Delft, Frank 


Selectivity is a crucial property in small molecule development. Binding site comparisons within a protein family are a key piece of information when aiming to modulate the selectivity profile of a compound. Binding site differences can be exploited to confer selectivity for a specific target, while shared areas can provide insights into polypharmacology. As the quantity of structural data grows, automated methods are needed to process, summarize, and present these data to users. We present a computational method that provides quantitative and data-driven summaries of the available binding site information from an ensemble of structures of the same protein. The resulting ensemble maps identify the key interactions important for ligand binding in the ensemble. The comparison of ensemble maps of related proteins enables the identification of selectivity-determining regions within a protein family. We applied the method to three examples from the well-researched human bromodomain and kinase families, demonstrating that the method is able to identify selectivity-determining regions that have been used to introduce selectivity in past drug discovery campaigns. We then illustrate how the resulting maps can be used to automate comparisons across a target protein family.


Funder: Exscientia

Funder: Diamond Light Source

Funder: Kungliga Tekniska Hoegskolan

Funder: Chinese Center for Disease Control and Prevention

Funder: European Federation of Pharmaceutical Industries and Associations

Funder: European Commission

Funder: Kennedy Trust for Rheumatology Research

Funder: Ontario Institute for Cancer Research

Funder: Royal Institution for the Advancement of Learning McGill University

Funder: UCB


Binding Sites, Drug Discovery, Humans, Polypharmacology, Protein Domains, Proteins

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J Chem Inf Model

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American Chemical Society (ACS)
Research Councils UK (BB/P50466X/1, EP/ L016044/1)
Wellcome Trust (106169/ZZ14/Z, 106169/Z/14/Z)
Innovative Medicines Initiative (115766, 875510)