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A systematic approach to identify therapeutic effects of natural products based on human metabolite information

BACKGROUND: Natural products have been widely investigated in the drug development field. Their traditional use cases as medicinal agents and their resemblance of our endogenous compounds show the possibility of new drug development. Many researchers have focused on identifying therapeutic effects o...

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Autores principales: Noh, Kyungrin, Yoo, Sunyong, Lee, Doheon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998763/
https://www.ncbi.nlm.nih.gov/pubmed/29897322
http://dx.doi.org/10.1186/s12859-018-2196-0
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author Noh, Kyungrin
Yoo, Sunyong
Lee, Doheon
author_facet Noh, Kyungrin
Yoo, Sunyong
Lee, Doheon
author_sort Noh, Kyungrin
collection PubMed
description BACKGROUND: Natural products have been widely investigated in the drug development field. Their traditional use cases as medicinal agents and their resemblance of our endogenous compounds show the possibility of new drug development. Many researchers have focused on identifying therapeutic effects of natural products, yet the resemblance of natural products and human metabolites has been rarely touched. METHODS: We propose a novel method which predicts therapeutic effects of natural products based on their similarity with human metabolites. In this study, we compare the structure, target and phenotype similarities between natural products and human metabolites to capture molecular and phenotypic properties of both compounds. With the generated similarity features, we train support vector machine model to identify similar natural product and human metabolite pairs. The known functions of human metabolites are then mapped to the paired natural products to predict their therapeutic effects. RESULTS: With our selected three feature sets, structure, target and phenotype similarities, our trained model successfully paired similar natural products and human metabolites. When applied to the natural product derived drugs, we could successfully identify their indications with high specificity and sensitivity. We further validated the found therapeutic effects of natural products with the literature evidence. CONCLUSIONS: These results suggest that our model can match natural products to similar human metabolites and provide possible therapeutic effects of natural products. By utilizing the similar human metabolite information, we expect to find new indications of natural products which could not be covered by previous in silico methods.
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spelling pubmed-59987632018-06-25 A systematic approach to identify therapeutic effects of natural products based on human metabolite information Noh, Kyungrin Yoo, Sunyong Lee, Doheon BMC Bioinformatics Research BACKGROUND: Natural products have been widely investigated in the drug development field. Their traditional use cases as medicinal agents and their resemblance of our endogenous compounds show the possibility of new drug development. Many researchers have focused on identifying therapeutic effects of natural products, yet the resemblance of natural products and human metabolites has been rarely touched. METHODS: We propose a novel method which predicts therapeutic effects of natural products based on their similarity with human metabolites. In this study, we compare the structure, target and phenotype similarities between natural products and human metabolites to capture molecular and phenotypic properties of both compounds. With the generated similarity features, we train support vector machine model to identify similar natural product and human metabolite pairs. The known functions of human metabolites are then mapped to the paired natural products to predict their therapeutic effects. RESULTS: With our selected three feature sets, structure, target and phenotype similarities, our trained model successfully paired similar natural products and human metabolites. When applied to the natural product derived drugs, we could successfully identify their indications with high specificity and sensitivity. We further validated the found therapeutic effects of natural products with the literature evidence. CONCLUSIONS: These results suggest that our model can match natural products to similar human metabolites and provide possible therapeutic effects of natural products. By utilizing the similar human metabolite information, we expect to find new indications of natural products which could not be covered by previous in silico methods. BioMed Central 2018-06-13 /pmc/articles/PMC5998763/ /pubmed/29897322 http://dx.doi.org/10.1186/s12859-018-2196-0 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Noh, Kyungrin
Yoo, Sunyong
Lee, Doheon
A systematic approach to identify therapeutic effects of natural products based on human metabolite information
title A systematic approach to identify therapeutic effects of natural products based on human metabolite information
title_full A systematic approach to identify therapeutic effects of natural products based on human metabolite information
title_fullStr A systematic approach to identify therapeutic effects of natural products based on human metabolite information
title_full_unstemmed A systematic approach to identify therapeutic effects of natural products based on human metabolite information
title_short A systematic approach to identify therapeutic effects of natural products based on human metabolite information
title_sort systematic approach to identify therapeutic effects of natural products based on human metabolite information
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998763/
https://www.ncbi.nlm.nih.gov/pubmed/29897322
http://dx.doi.org/10.1186/s12859-018-2196-0
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