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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...

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Autores principales: Born, Jannis, Shoshan, Yoel, Huynh, Tien, Cornell, Wendy D., Martin, Eric J., Manica, Matteo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
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
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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.
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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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