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

[Image: see text] 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 spec...

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Autores principales: Smilova, Mihaela D., Curran, Peter R., Radoux, Chris J., von Delft, Frank, Cole, Jason C., Bradley, Anthony R., Marsden, Brian D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790751/
https://www.ncbi.nlm.nih.gov/pubmed/35020376
http://dx.doi.org/10.1021/acs.jcim.1c00823
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author Smilova, Mihaela D.
Curran, Peter R.
Radoux, Chris J.
von Delft, Frank
Cole, Jason C.
Bradley, Anthony R.
Marsden, Brian D.
author_facet Smilova, Mihaela D.
Curran, Peter R.
Radoux, Chris J.
von Delft, Frank
Cole, Jason C.
Bradley, Anthony R.
Marsden, Brian D.
author_sort Smilova, Mihaela D.
collection PubMed
description [Image: see text] 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.
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spelling pubmed-87907512022-01-27 Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins Smilova, Mihaela D. Curran, Peter R. Radoux, Chris J. von Delft, Frank Cole, Jason C. Bradley, Anthony R. Marsden, Brian D. J Chem Inf Model [Image: see text] 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. American Chemical Society 2022-01-12 2022-01-24 /pmc/articles/PMC8790751/ /pubmed/35020376 http://dx.doi.org/10.1021/acs.jcim.1c00823 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Smilova, Mihaela D.
Curran, Peter R.
Radoux, Chris J.
von Delft, Frank
Cole, Jason C.
Bradley, Anthony R.
Marsden, Brian D.
Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins
title Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins
title_full Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins
title_fullStr Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins
title_full_unstemmed Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins
title_short Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins
title_sort fragment hotspot mapping to identify selectivity-determining regions between related proteins
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790751/
https://www.ncbi.nlm.nih.gov/pubmed/35020376
http://dx.doi.org/10.1021/acs.jcim.1c00823
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