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Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction
Ligand-based models can be used in drug discovery to obtain an early indication of potential off-target interactions that could be linked to adverse effects. Another application is to combine such models into a panel, allowing to compare and search for compounds with similar profiles. Most contempor...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233526/ https://www.ncbi.nlm.nih.gov/pubmed/30459617 http://dx.doi.org/10.3389/fphar.2018.01256 |
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author | Lampa, Samuel Alvarsson, Jonathan Arvidsson Mc Shane, Staffan Berg, Arvid Ahlberg, Ernst Spjuth, Ola |
author_facet | Lampa, Samuel Alvarsson, Jonathan Arvidsson Mc Shane, Staffan Berg, Arvid Ahlberg, Ernst Spjuth, Ola |
author_sort | Lampa, Samuel |
collection | PubMed |
description | Ligand-based models can be used in drug discovery to obtain an early indication of potential off-target interactions that could be linked to adverse effects. Another application is to combine such models into a panel, allowing to compare and search for compounds with similar profiles. Most contemporary methods and implementations however lack valid measures of confidence in their predictions, and only provide point predictions. We here describe a methodology that uses Conformal Prediction for predicting off-target interactions, with models trained on data from 31 targets in the ExCAPE-DB dataset selected for their utility in broad early hazard assessment. Chemicals were represented by the signature molecular descriptor and support vector machines were used as the underlying machine learning method. By using conformal prediction, the results from predictions come in the form of confidence p-values for each class. The full pre-processing and model training process is openly available as scientific workflows on GitHub, rendering it fully reproducible. We illustrate the usefulness of the developed methodology on a set of compounds extracted from DrugBank. The resulting models are published online and are available via a graphical web interface and an OpenAPI interface for programmatic access. |
format | Online Article Text |
id | pubmed-6233526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-62335262018-11-20 Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction Lampa, Samuel Alvarsson, Jonathan Arvidsson Mc Shane, Staffan Berg, Arvid Ahlberg, Ernst Spjuth, Ola Front Pharmacol Pharmacology Ligand-based models can be used in drug discovery to obtain an early indication of potential off-target interactions that could be linked to adverse effects. Another application is to combine such models into a panel, allowing to compare and search for compounds with similar profiles. Most contemporary methods and implementations however lack valid measures of confidence in their predictions, and only provide point predictions. We here describe a methodology that uses Conformal Prediction for predicting off-target interactions, with models trained on data from 31 targets in the ExCAPE-DB dataset selected for their utility in broad early hazard assessment. Chemicals were represented by the signature molecular descriptor and support vector machines were used as the underlying machine learning method. By using conformal prediction, the results from predictions come in the form of confidence p-values for each class. The full pre-processing and model training process is openly available as scientific workflows on GitHub, rendering it fully reproducible. We illustrate the usefulness of the developed methodology on a set of compounds extracted from DrugBank. The resulting models are published online and are available via a graphical web interface and an OpenAPI interface for programmatic access. Frontiers Media S.A. 2018-11-06 /pmc/articles/PMC6233526/ /pubmed/30459617 http://dx.doi.org/10.3389/fphar.2018.01256 Text en Copyright © 2018 Lampa, Alvarsson, Arvidsson Mc Shane, Berg, Ahlberg and Spjuth. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Lampa, Samuel Alvarsson, Jonathan Arvidsson Mc Shane, Staffan Berg, Arvid Ahlberg, Ernst Spjuth, Ola Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction |
title | Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction |
title_full | Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction |
title_fullStr | Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction |
title_full_unstemmed | Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction |
title_short | Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction |
title_sort | predicting off-target binding profiles with confidence using conformal prediction |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233526/ https://www.ncbi.nlm.nih.gov/pubmed/30459617 http://dx.doi.org/10.3389/fphar.2018.01256 |
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