[Functional orientation of Moringa leaves based on text mining and molecular docking technology]

Area of Science:

• Pharmacology and Bioinformatics
• Computational Drug Discovery
• Ethnomedicine Research

Background:

• Moringa leaves are a rich source of bioactive compounds with potential therapeutic applications.
• Traditional uses of Moringa necessitate scientific validation for modern medicine.
• Understanding the molecular mechanisms of Moringa's efficacy is crucial for its wider adoption.

Purpose of the Study:

• To develop and apply a novel computational method for functional orientation of Moringa leaves.
• To identify potential therapeutic indications, active components, and molecular targets of Moringa leaves.
• To provide a reference for the utilization of medicinal plant resources.

Main Methods:

• Text mining of PubMedplus and Arrowsmith for literature analysis and target identification.
• SwissADME and systemsDock for filtering active components and performing molecular docking.
• DAVID database for Gene Ontology (GO) functional annotation of predicted targets.

Main Results:

• Identified potential indications for Moringa leaves including tumor, diabetes, and digestive diseases.
• Screened 25 active components and 12 potential effective molecular targets.
• Predicted mechanisms involve modulation of G protein-coupled receptors and inflammatory responses.

Conclusions:

• The integrated text mining and molecular docking approach is effective for functional orientation of medicinal plants.
• Moringa leaves show promise for treating metabolic and inflammatory diseases.
• This study offers a valuable framework for exploring other medicinal plant resources.