Project Details
Projekt
Curated database of candidate therapeutics for the activation of CFTR-mediated ion conductance (CandActCFTR)
Subject Area
Medical Informatics and Medical Bioinformatics
Term
from 2016 to 2024
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 315063128
Cystic fibrosis (CF) is a genetic disease, caused by CFTR which encodes a chloride and bicarbonate transporter expressed in exocrine epithelia throughout the body. Since a few years, therapeutics are available that directly target dysfunctional CFTR. While CFTR mutation-specific therapeutics became available, research for more effective substances are ongoing. Within the last funding period, we have established CandActCFTR as a comprehensive research tool combining information on a growing amount of CFTR acting substances from different sources, mainly retrieved from publications in scientific journals, abstracts and presentations on scientific meetings. CandActCFTR in its current form can be installed and operated at other sites. Until 10/2018, we could collect data on more than 3000 CFTR-relevant substances from public sources. We have implemented a principle component analysis to visualize the similarity of substances and we have handled requests from the CF community to answer whether a certain substance is similar in structure to a CFTR activator listed in CandActCFTR. Now, our work program to extend CandActCFTR is structured into five work packages: extend the functionality of the CandActCFTR database, for instance, by including a user access management which will facilitate data sharing in the CF community in the future. We will develop the means to predict the interaction between CandActCFTR substances and CFTR by using molecular dynamics trajectory organization and annotation and we will use gene expression data to compare differentially expressed genes to gene sets with known relevance for CFTR function. This will help us to rank putative therapeutic substances according to their potential to modify the cellular transcriptome in favor of CFTR function. Finally, we will use the information compiled in CandActCFTR to test five substance combinations in five bioassays, relying on cooperation partners in the community. This will answer the question whether the data collection, the annotation of the chemical space and the prediction tools are useful to select therapeutics with a relevant potential compared to established CFTR therapeutics such as Ivacaftor, Lumacaftor and Tezacaftor (© Vertex, Boston, Massachusetts). The application CandActBase, adaptable to other use cases than CFTR compound analysis, and the CandActCFTR data content is provided at https://gitlab.gwdg.de/mnieter1/CandActBase.
DFG Programme
Research Grants
