Comprehensive Analysis of Chemical Structures That Have Been Tested as CFTR Activating Substances in a Publicly Available Database CandActCFTR

Abstract

Background: Cystic fibrosis (CF) is a genetic disease caused by mutations in CFTR, which encodes a chloride and bicarbonate transporter expressed in exocrine epithelia throughout the body. Recently, some therapeutics became available that directly target dysfunctional CFTR, yet research for more effective substances is ongoing. The database CandActCFTR aims to provide detailed and comprehensive information on candidate therapeutics for the activation of CFTR-mediated ion conductance aiding systems-biology approaches to identify substances that will synergistically activate CFTR-mediated ion conductance based on published data.Results: Until 10/2020, we derived data from 108 publications on 3,109 CFTR-relevant substances via the literature database PubMed and further 666 substances via ChEMBL; only 19 substances were shared between these sources. One hundred and forty-five molecules do not have a corresponding entry in PubChem or ChemSpider, which indicates that there currently is no single comprehensive database on chemical substances in the public domain. Apart from basic data on all compounds, we have visualized the chemical space derived from their chemical descriptors via a principal component analysis annotated for CFTR-relevant biological categories. Our online query tools enable the search for most similar compounds and provide the relevant annotations in a structured way. The integration of the KNIME software environment in the back-end facilitates a fast and user-friendly maintenance of the provided data sets and a quick extension with new functionalities, e.g., new analysis routines. CandActBase automatically integrates information from other online sources, such as synonyms from PubChem and provides links to other resources like ChEMBL or the source publications.Conclusion: CandActCFTR aims to establish a database model of candidate cystic fibrosis therapeutics for the activation of CFTR-mediated ion conductance to merge data from publicly available sources. Using CandActBase, our strategy to represent data from several internet resources in a merged and organized form can also be applied to other use cases. For substances tested as CFTR activating compounds, the search function allows users to check if a specific compound or a closely related substance was already tested in the CF field. The acquired information on tested substances will assist in the identification of the most promising candidates for future therapeutics.

Complementary Dual Approach for In Silico Target Identification of Potential Pharmaceutical Compounds in Cystic Fibrosis

“…In order to suggest possible mechanisms of actions of active compounds in the CandActCFTR database [ 43 ], possible protein targets that are involved in CFTR biogenesis were selected from the CFTR Lifecycle Map [ 45 ]. For this purpose, the Protein Data Bank [ 52 ] was queried for experimental X-ray or CryoEM structures of all proteins within the CFTR Lifecycle Map.…”

“…All active compounds from the CandActCFTR [ 42 , 43 ] database were docked against all 35 targets using the Smina [ 56 ] and QuickVina-W (qvina-W) [ 57 ] docking programs. After docking, two methods (2.1) were used for post-processing.…”

“…In order to identify targets for the active compounds of the CF-specific compound database CandActCFTR [ 42 , 43 ], 37 potentially relevant protein targets were used for reverse docking. The proteins were selected using the CFTR lifecycle map [ 45 ], a systems biology model of the CFTR lifecycle.…”

“…Thousands of compounds are being tested in different cell-assays, often in high-throughput screens, leading to large amounts of data and various candidate substances [ 20 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. In order to structure and collect the compounds tested as CFTR modulators, we previously developed the publicly available database CandActCFTR (candactcftr.ams.med.uni-goettingen.de), where compounds are annotated and categorized according to various characteristics, including their mode of action and order of interaction with CFTR [ 42 , 43 ]. When analysing the data, it becomes apparent that for about 70% of the active compounds, it is unknown whether they affect CFTR directly through physical interaction, or indirectly through its interactome.…”

Integrating Text Mining into the Curation of Disease Maps

“…To make our Cytoscape.js instance accessible, we used Grails and our previously developed CandActBase [ 19 ] as an underlying framework. We used the AJAX (Asynchronous JavaScript and XML) protocol to dynamically load data into a JavaScript application from a web server [ 20 ].…”