How This Workflow Works
This workflow automates the evaluation of a compound library by calculating key molecular properties and applying two well-known drug-likeness rules. It tags and filters compounds based on their likelihood to meet pharmacokinetic criteria, outputs the results, and provides interactive visualizations to support decision-making.
Key Features:
- Automate the application of drug-likeness rules to large compound libraries
- Flag and filter compounds based on their suitability for further research
- Summarize and visualize pass/fail results for rapid assessment
- Export filtered compound lists for downstream use
Step-by-step:
1. Calculate Molecular Properties and Apply Drug-Likeness Rules:
The workflow calculates relevant molecular descriptors for each compound, such as molecular weight and hydrogen bond donors and acceptors. It then applies two exemplary rules—Lipinski's Rule of Five and the Rule of Three—to assess each compound's suitability for drug development.
2. Tag and Categorize Compounds:
Each compound is tagged according to which rules it passes or fails. The workflow aggregates these results, assigns clear pass/fail labels, and sorts compounds based on how many criteria they meet.
3. Filter and Export Compound Lists:
Based on the tagging, the workflow filters the compounds into groups—those passing all rules, those passing specific rules, and those failing both. It then exports these lists as separate files for further analysis or experimental planning.
4. Visualize and Share Insights:
The workflow generates interactive dashboards and visualizations, including pie charts, bar charts, and property plots. These tools help users quickly understand the distribution of pass/fail outcomes and explore relationships between compound properties and rule compliance.