Abstract
The MINERVA platform is currently the most widely used platform for visualizing and providing access to disease maps. Disease maps are systems biological maps of molecular interactions relevant in a certain disease context, where they can be used to support drug discovery. For this purpose, we extended MINERVA’s own drug and chemical search using the MINERVA plugin starter kit. We developed a plugin to provide a linkage between disease maps in MINERVA and application-specific databases of candidate therapeutics. The plugin has three main functionalities; one shows all the targets of all the compounds in the database, the second is a compound-based search to highlight targets of specific compounds, and the third can be used to find compounds that affect a certain target. As a use case, we applied the plugin to link a disease map and compound database we previously established in the context of cystic fibrosis and, herein, point out possible issues and difficulties. The plugin is publicly available on GitLab; the use-case application to cystic fibrosis, connecting disease maps and the compound database CandActCFTR, is available online.
Highlights
One of the main aims of systems biology and systems medicine is to understand and model molecular mechanisms in diseases, which can support the development of novel therapeutics
Disease maps can be used to elucidate the mechanism of action of potential therapeutics that have been tested in high-throughput screens and identify potential side-effects or adverse reactions that cannot be detected during the screening process
We developed a MINEVRA plugin to link disease maps and application-specific compound databases, using the CandActCFTR database designed for cystic fibrosis as a use case
Summary
One of the main aims of systems biology and systems medicine is to understand and model molecular mechanisms in diseases, which can support the development of novel therapeutics For this purpose, disease maps are being developed to represent existing knowledge on disease mechanisms in a computationally readable and comprehensive manner [1]. A common method in the field of drug discovery is high-throughput screens, where hundreds of small molecules are tested in a certain disease context. These often lead to promising lead substances; the means by which the compounds achieve their effects remain unclear in most cases. Disease maps can be used to elucidate the mechanism of action of potential therapeutics that have been tested in high-throughput screens and identify potential side-effects or adverse reactions that cannot be detected during the screening process
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