Reproducible Computational Workflow for Drug Discovery to Standardize Network Pharmacology and Molecular Docking...

Area of Science:

• Computational drug discovery
• Pharmacology and toxicology
• Bioinformatics and systems biology

Background:

• Network pharmacology and molecular docking are crucial for drug discovery but suffer from reproducibility issues due to fragmented workflows.
• Inconsistent operations in computational drug discovery pipelines hinder reliable results and cross-study comparisons.

Purpose of the Study:

• To develop a standardized and reproducible protocol integrating network pharmacology and molecular docking for efficient drug screening and mechanism exploration.
• To establish a unified framework that enhances the reliability and comparability of computational drug discovery studies.

Main Methods:

• A three-phase workflow: data preparation (ADMET filtering, target identification), computational analysis (enrichment analyses, network analysis, dual-strategy molecular docking), and validation (MD simulations).
• Employs two molecular docking strategies: a two-step approach (AutoDock Vina + YASARA) for high-throughput screening and re-docking, and a one-step YASARA strategy for efficiency.
• Utilizes standardized molecular dynamics simulations with RMSD and RMSF metrics for evaluating ligand-protein complex stability.

Main Results:

• The described protocol provides a reproducible framework for drug screening and mechanism exploration, addressing workflow fragmentation.
• The dual-strategy docking approach optimizes screening efficiency while maintaining accuracy and compatibility with downstream analyses like molecular dynamics.
• Standardized validation metrics ensure the reliability of molecular dynamics simulations for assessing complex stability.

Conclusions:

• This unified, reproducible pipeline significantly enhances the reliability of network pharmacology and molecular docking studies.
• The framework facilitates cross-study comparisons, advancing the field of computational drug discovery.
• The protocol offers a robust solution for consistent and dependable results in identifying novel drug candidates and their mechanisms.