Large-Scale Target Identification of Herbal Medicine Using a Reverse Docking Approach

Area of Science:

• Computational Biology
• Pharmacology
• Natural Products Chemistry

Background:

• Herbal medicine has a long history of use, but understanding its therapeutic mechanisms is hindered by unclear protein targets.
• This lack of target identification slows down the discovery of new drugs from natural products.

Purpose of the Study:

• To develop a novel computational pipeline for the de novo identification of protein targets for herbal ingredients.
• To facilitate efficient and large-scale target exploration in herbal medicine research.

Main Methods:

• The pipeline integrates pharmacophore comparison and high-throughput reverse ligand-protein docking simulations.
• Validation was performed using three traditional Chinese medicine compounds: acteoside, quercetin, and epigallocatechin gallate.

Main Results:

• The pipeline successfully identified known protein targets for the selected herbal ingredients.
• Structural analyses confirmed the accuracy of predicted ligand-target interactions, including binding pockets and modes.
• Pharmacological networks were constructed to illustrate the mechanisms of action.

Conclusions:

• The developed computational pipeline offers an efficient and cost-effective approach for identifying herbal medicine targets.
• This tool is valuable for precise drug discovery and drug repurposing from natural products.