Cargando…
In silico profiling of systemic effects of drugs to predict unexpected interactions
Identifying unexpected drug interactions is an essential step in drug development. Most studies focus on predicting whether a drug pair interacts or is effective on a certain disease without considering the mechanism of action (MoA). Here, we introduce a novel method to infer effects and interaction...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5785495/ https://www.ncbi.nlm.nih.gov/pubmed/29371651 http://dx.doi.org/10.1038/s41598-018-19614-5 |
_version_ | 1783295616409927680 |
---|---|
author | Yoo, Sunyong Noh, Kyungrin Shin, Moonshik Park, Junseok Lee, Kwang-Hyung Nam, Hojung Lee, Doheon |
author_facet | Yoo, Sunyong Noh, Kyungrin Shin, Moonshik Park, Junseok Lee, Kwang-Hyung Nam, Hojung Lee, Doheon |
author_sort | Yoo, Sunyong |
collection | PubMed |
description | Identifying unexpected drug interactions is an essential step in drug development. Most studies focus on predicting whether a drug pair interacts or is effective on a certain disease without considering the mechanism of action (MoA). Here, we introduce a novel method to infer effects and interactions of drug pairs with MoA based on the profiling of systemic effects of drugs. By investigating propagated drug effects from the molecular and phenotypic networks, we constructed profiles of 5,441 approved and investigational drugs for 3,833 phenotypes. Our analysis indicates that highly connected phenotypes between drug profiles represent the potential effects of drug pairs and the drug pairs with strong potential effects are more likely to interact. When applied to drug interactions with verified effects, both therapeutic and adverse effects have been successfully identified with high specificity and sensitivity. Finally, tracing drug interactions in molecular and phenotypic networks allows us to understand the MoA. |
format | Online Article Text |
id | pubmed-5785495 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57854952018-02-07 In silico profiling of systemic effects of drugs to predict unexpected interactions Yoo, Sunyong Noh, Kyungrin Shin, Moonshik Park, Junseok Lee, Kwang-Hyung Nam, Hojung Lee, Doheon Sci Rep Article Identifying unexpected drug interactions is an essential step in drug development. Most studies focus on predicting whether a drug pair interacts or is effective on a certain disease without considering the mechanism of action (MoA). Here, we introduce a novel method to infer effects and interactions of drug pairs with MoA based on the profiling of systemic effects of drugs. By investigating propagated drug effects from the molecular and phenotypic networks, we constructed profiles of 5,441 approved and investigational drugs for 3,833 phenotypes. Our analysis indicates that highly connected phenotypes between drug profiles represent the potential effects of drug pairs and the drug pairs with strong potential effects are more likely to interact. When applied to drug interactions with verified effects, both therapeutic and adverse effects have been successfully identified with high specificity and sensitivity. Finally, tracing drug interactions in molecular and phenotypic networks allows us to understand the MoA. Nature Publishing Group UK 2018-01-25 /pmc/articles/PMC5785495/ /pubmed/29371651 http://dx.doi.org/10.1038/s41598-018-19614-5 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Yoo, Sunyong Noh, Kyungrin Shin, Moonshik Park, Junseok Lee, Kwang-Hyung Nam, Hojung Lee, Doheon In silico profiling of systemic effects of drugs to predict unexpected interactions |
title | In silico profiling of systemic effects of drugs to predict unexpected interactions |
title_full | In silico profiling of systemic effects of drugs to predict unexpected interactions |
title_fullStr | In silico profiling of systemic effects of drugs to predict unexpected interactions |
title_full_unstemmed | In silico profiling of systemic effects of drugs to predict unexpected interactions |
title_short | In silico profiling of systemic effects of drugs to predict unexpected interactions |
title_sort | in silico profiling of systemic effects of drugs to predict unexpected interactions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5785495/ https://www.ncbi.nlm.nih.gov/pubmed/29371651 http://dx.doi.org/10.1038/s41598-018-19614-5 |
work_keys_str_mv | AT yoosunyong insilicoprofilingofsystemiceffectsofdrugstopredictunexpectedinteractions AT nohkyungrin insilicoprofilingofsystemiceffectsofdrugstopredictunexpectedinteractions AT shinmoonshik insilicoprofilingofsystemiceffectsofdrugstopredictunexpectedinteractions AT parkjunseok insilicoprofilingofsystemiceffectsofdrugstopredictunexpectedinteractions AT leekwanghyung insilicoprofilingofsystemiceffectsofdrugstopredictunexpectedinteractions AT namhojung insilicoprofilingofsystemiceffectsofdrugstopredictunexpectedinteractions AT leedoheon insilicoprofilingofsystemiceffectsofdrugstopredictunexpectedinteractions |