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Forskolin-induced Swelling in Intestinal Organoids: An In Vitro Assay for Assessing Drug Response in Cystic Fibrosis Patients
Published on: February 11, 2017
Complementary Dual Approach for In Silico Target Identification of Potential Pharmaceutical Compounds in Cystic
Liza Vinhoven1, Frauke Stanke2,3, Sylvia Hafkemeyer4
1Department of Medical Bioinformatics, University Medical Center Göttingen, Goldschmidtstraße 1, 37077 Göttingen, Germany.
Abstract:
Cystic fibrosis is a genetic disease caused by mutation of the CFTR gene, which encodes a chloride and bicarbonate transporter in epithelial cells. Due to the vast range of geno- and phenotypes, it is difficult to find causative treatments; however, small-molecule therapeutics have been clinically approved in the last decade. Still, the search for novel therapeutics is ongoing, and thousands of compounds are being tested in different assays, often leaving their mechanism of action unknown. Here, we bring together a CFTR-specific compound database (CandActCFTR) and systems biology model (CFTR Lifecycle Map) to identify the targets of the most promising compounds. We use a dual inverse screening approach, where we employ target- and ligand-based methods to suggest targets of 309 active compounds in the database amongst 90 protein targets from the systems biology model. Overall, we identified 1038 potential target-compound pairings and were able to suggest targets for all 309 active compounds in the database.
Insights
This study identifies potential drug targets for cystic fibrosis (CF) by analyzing compounds that affect the CFTR protein. Researchers mapped 309 compounds to 90 potential targets, advancing the search for new CFTR therapies.
Area of Science:
- Biochemistry
- Genetics
- Systems Biology
Background:
- Cystic fibrosis (CF) is a genetic disorder caused by mutations in the CFTR gene, impacting epithelial cell function.
- Developing effective treatments for CF is challenging due to diverse patient phenotypes.
- While small-molecule drugs have emerged, understanding their mechanisms of action is crucial for discovering novel therapeutics.
Purpose of the Study:
- To identify the molecular targets of active compounds relevant to cystic fibrosis.
- To integrate a CFTR-specific compound database with a systems biology model for drug discovery.
- To systematically predict potential drug-target interactions for novel CFTR therapeutics.
Main Methods:
- Developed and utilized a CFTR-specific compound database (CandActCFTR).
- Employed a systems biology model, the CFTR Lifecycle Map, comprising 90 protein targets.
- Applied a dual inverse screening approach combining target- and ligand-based methods.
Main Results:
- Identified 1038 potential target-compound pairings.
- Successfully suggested targets for all 309 active compounds within the CandActCFTR database.
- Provided a comprehensive resource for understanding compound mechanisms in CFTR research.
Conclusions:
- The integrated approach effectively predicts drug targets for CFTR-related compounds.
- This methodology accelerates the identification of novel therapeutic candidates for cystic fibrosis.
- The study provides a foundation for further investigation into compound mechanisms and drug development for CF.
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