Tissue‐Specific Analysis of Pharmacological Pathways

Understanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue‐naïve assumptions. Many target proteins, however, have tissue‐specific expression. A systematic study connecting drugs to target...

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Main Authors: Yun Hao, Kayla Quinnies, Ronald Realubit, Charles Karan, Nicholas P. Tatonetti
Format: Article
Language:English
Published: Wiley 2018-07-01
Series:CPT: Pharmacometrics & Systems Pharmacology
Online Access:https://doi.org/10.1002/psp4.12305
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spelling doaj-ad105b89fb6f4dbd80c8fe8687f703e72020-11-25T03:46:59ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062018-07-017745346310.1002/psp4.12305Tissue‐Specific Analysis of Pharmacological PathwaysYun Hao0Kayla Quinnies1Ronald Realubit2Charles Karan3Nicholas P. Tatonetti4Departments of Biomedical InformaticsSystems Biology, and Medicine, Columbia UniversityNew York New York USADepartments of Biomedical InformaticsSystems Biology, and Medicine, Columbia UniversityNew York New York USAColumbia Genome Center, Columbia UniversityNew York New York USAColumbia Genome Center, Columbia UniversityNew York New York USADepartments of Biomedical InformaticsSystems Biology, and Medicine, Columbia UniversityNew York New York USAUnderstanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue‐naïve assumptions. Many target proteins, however, have tissue‐specific expression. A systematic study connecting drugs to target pathways in in vivo human tissues is needed. We introduced a data‐driven method that integrates drug‐target relationships with gene expression, protein‐protein interaction, and pathway annotation data. We applied our method to four independent genomewide expression datasets and built 467,396 connections between 1,034 drugs and 954 pathways in 259 human tissues or cell lines. We validated our results using data from L1000 and Pharmacogenomics Knowledgebase (PharmGKB), and observed high precision and recall. We predicted and tested anticoagulant effects of 22 compounds experimentally that were previously unknown, and used clinical data to validate these effects retrospectively. Our systematic study provides a better understanding of the cellular response to drugs and can be applied to many research topics in systems pharmacology.https://doi.org/10.1002/psp4.12305
collection DOAJ
language English
format Article
sources DOAJ
author Yun Hao
Kayla Quinnies
Ronald Realubit
Charles Karan
Nicholas P. Tatonetti
spellingShingle Yun Hao
Kayla Quinnies
Ronald Realubit
Charles Karan
Nicholas P. Tatonetti
Tissue‐Specific Analysis of Pharmacological Pathways
CPT: Pharmacometrics & Systems Pharmacology
author_facet Yun Hao
Kayla Quinnies
Ronald Realubit
Charles Karan
Nicholas P. Tatonetti
author_sort Yun Hao
title Tissue‐Specific Analysis of Pharmacological Pathways
title_short Tissue‐Specific Analysis of Pharmacological Pathways
title_full Tissue‐Specific Analysis of Pharmacological Pathways
title_fullStr Tissue‐Specific Analysis of Pharmacological Pathways
title_full_unstemmed Tissue‐Specific Analysis of Pharmacological Pathways
title_sort tissue‐specific analysis of pharmacological pathways
publisher Wiley
series CPT: Pharmacometrics & Systems Pharmacology
issn 2163-8306
publishDate 2018-07-01
description Understanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue‐naïve assumptions. Many target proteins, however, have tissue‐specific expression. A systematic study connecting drugs to target pathways in in vivo human tissues is needed. We introduced a data‐driven method that integrates drug‐target relationships with gene expression, protein‐protein interaction, and pathway annotation data. We applied our method to four independent genomewide expression datasets and built 467,396 connections between 1,034 drugs and 954 pathways in 259 human tissues or cell lines. We validated our results using data from L1000 and Pharmacogenomics Knowledgebase (PharmGKB), and observed high precision and recall. We predicted and tested anticoagulant effects of 22 compounds experimentally that were previously unknown, and used clinical data to validate these effects retrospectively. Our systematic study provides a better understanding of the cellular response to drugs and can be applied to many research topics in systems pharmacology.
url https://doi.org/10.1002/psp4.12305
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AT nicholasptatonetti tissuespecificanalysisofpharmacologicalpathways
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