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On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction
[Image: see text] Recent work showed that active site rather than full-protein-sequence information improves predictive performance in kinase-ligand binding affinity prediction. To refine the notion of an “active site”, we here propose and compare multiple definitions. We report significant evidence...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516689/ https://www.ncbi.nlm.nih.gov/pubmed/36098536 http://dx.doi.org/10.1021/acs.jcim.2c00840 |
_version_ | 1784798763304353792 |
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author | Born, Jannis Shoshan, Yoel Huynh, Tien Cornell, Wendy D. Martin, Eric J. Manica, Matteo |
author_facet | Born, Jannis Shoshan, Yoel Huynh, Tien Cornell, Wendy D. Martin, Eric J. Manica, Matteo |
author_sort | Born, Jannis |
collection | PubMed |
description | [Image: see text] Recent work showed that active site rather than full-protein-sequence information improves predictive performance in kinase-ligand binding affinity prediction. To refine the notion of an “active site”, we here propose and compare multiple definitions. We report significant evidence that our novel definition is superior to previous definitions and better models of ATP-noncompetitive inhibitors. Moreover, we leverage the discontiguity of the active site sequence to motivate novel protein-sequence augmentation strategies and find that combining them further improves performance. |
format | Online Article Text |
id | pubmed-9516689 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-95166892022-09-29 On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction Born, Jannis Shoshan, Yoel Huynh, Tien Cornell, Wendy D. Martin, Eric J. Manica, Matteo J Chem Inf Model [Image: see text] Recent work showed that active site rather than full-protein-sequence information improves predictive performance in kinase-ligand binding affinity prediction. To refine the notion of an “active site”, we here propose and compare multiple definitions. We report significant evidence that our novel definition is superior to previous definitions and better models of ATP-noncompetitive inhibitors. Moreover, we leverage the discontiguity of the active site sequence to motivate novel protein-sequence augmentation strategies and find that combining them further improves performance. American Chemical Society 2022-09-13 2022-09-26 /pmc/articles/PMC9516689/ /pubmed/36098536 http://dx.doi.org/10.1021/acs.jcim.2c00840 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 | Born, Jannis Shoshan, Yoel Huynh, Tien Cornell, Wendy D. Martin, Eric J. Manica, Matteo On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction |
title | On the Choice of
Active Site Sequences for Kinase-Ligand
Affinity Prediction |
title_full | On the Choice of
Active Site Sequences for Kinase-Ligand
Affinity Prediction |
title_fullStr | On the Choice of
Active Site Sequences for Kinase-Ligand
Affinity Prediction |
title_full_unstemmed | On the Choice of
Active Site Sequences for Kinase-Ligand
Affinity Prediction |
title_short | On the Choice of
Active Site Sequences for Kinase-Ligand
Affinity Prediction |
title_sort | on the choice of
active site sequences for kinase-ligand
affinity prediction |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516689/ https://www.ncbi.nlm.nih.gov/pubmed/36098536 http://dx.doi.org/10.1021/acs.jcim.2c00840 |
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