Mapping Compound Databases to Disease Maps-A MINERVA Plugin for CandActBase

Area of Science:

• Systems biology
• Pharmacology
• Bioinformatics

Background:

• MINERVA is a key platform for visualizing disease maps, which are systems biological maps of molecular interactions.
• Disease maps are valuable tools for supporting drug discovery efforts.
• Existing functionalities in MINERVA lack direct integration with specific therapeutic databases.

Purpose of the Study:

• To extend MINERVA's drug and chemical search capabilities.
• To develop a plugin for linking disease maps with application-specific candidate therapeutic databases.
• To facilitate drug discovery by connecting molecular interaction data with potential therapeutics.

Main Methods:

• Utilized the MINERVA plugin starter kit to develop a new plugin.
• Implemented three core functionalities: compound-to-target mapping, target-to-compound searching, and compound-specific target identification.
• Applied the plugin to a cystic fibrosis disease map and a related compound database (CandActCFTR) as a use case.

Main Results:

• Successfully developed a plugin that integrates MINERVA disease maps with external therapeutic databases.
• The plugin enables efficient searching of compound-target interactions, aiding in the identification of potential drug candidates.
• A use case demonstrated the plugin's application in cystic fibrosis research, highlighting practical implementation aspects and challenges.

Conclusions:

• The developed MINERVA plugin enhances drug discovery by bridging disease maps and therapeutic compound databases.
• The plugin's functionalities streamline the process of identifying therapeutic targets and candidate compounds.
• The publicly available plugin and cystic fibrosis use case provide a valuable resource for researchers in systems biology and drug development.