bioassayR: Cross-Target Analysis of Small Molecule Bioactivity

Area of Science:

• Computational Biology
• Bioinformatics
• Drug Discovery

Background:

• Publicly available small molecule bioactivity data is rapidly expanding.
• Lack of suitable software hinders cross-target analysis for druggability and selectivity.
• Systematic data leverage for drug discovery is challenging.

Purpose of the Study:

• To develop a computational tool for large-scale bioassay data analysis.
• To enable simultaneous analysis of diverse compounds and biological targets.
• To facilitate assessment of target druggability and compound selectivity.

Main Methods:

• Developed bioassayR, an open-source R/Bioconductor package.
• Implemented support for large-scale cross-target analyses of public and custom bioassays.
• Enabled generation of high throughput screening fingerprints (HTSFPs).
• Included an optional preloaded database of public bioactivity data.

Main Results:

• bioassayR allows simultaneous analysis of thousands of bioassay experiments.
• The tool supports both public and custom bioassay data.
• High throughput screening fingerprints (HTSFPs) can be generated.
• Access to substantial public bioactivity data is provided.

Conclusions:

• bioassayR addresses the need for cross-target analysis software in drug discovery.
• The tool enhances the systematic leverage of public bioactivity screening data.
• bioassayR facilitates assessment of target druggability and compound selectivity.
• An open-source R/Bioconductor package is now available for researchers.