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

Published version
Peer-reviewed

Type

Article

Change log

Authors

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

Abstract

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.

Description

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

Keywords

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

Journal Title

J Chem Inf Model

Conference Name

Journal ISSN

1549-9596
1549-960X

Volume Title

62

Publisher

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