TCMSP

TCMSP provides a database and analysis platform for network pharmacology that identifies active compounds in traditional Chinese medicine and predicts their protein targets to support mechanistic studies.

Key Features:

• Compound screening: Screens active components of traditional herbs, exemplified by identification of 23 active compounds in Psoralea corylifolia.
• Target prediction: Predicts potential protein targets, initially yielding 162 candidate targets for P. corylifolia.
• Data integration: Integrates literature and database records including STITCH, SwissTargetPrediction, and PubChem for compound and target information.
• Network pharmacology analysis: Performs network pharmacology analyses to refine predicted targets, reducing 162 candidates to 71 key targets.
• Network construction and visualization: Constructs target networks related to herbs and biological processes and exports networks for analysis in Cytoscape.
• Biological entity mapping: Links identified compounds (bavachalcone, psoralen, bavachinin, neobavaisoflavone, methoxsalen, psoradin, bakuchiol, angelicin) to predicted targets including PPARγ and AhR.
• Experimental prioritization: Produces target lists used to prioritize experimental validation, as demonstrated by western blot and immunofluorescence in MC3T3-E1 cells.

Scientific Applications:

• Osteogenic mechanism elucidation: Identifies osteogenesis-related active compounds and their targets in Psoralea corylifolia to investigate mechanisms relevant to osteoporosis.
• Target network construction: Builds target networks for P. corylifolia and osteogenic differentiation to reveal interaction modules and key proteins.
• Bioactive compound identification: Highlights specific bioactive compounds (bavachalcone, psoralen, bavachinin, neobavaisoflavone, methoxsalen, psoradin, bakuchiol, angelicin) implicated in bone formation.
• Target prioritization for validation: Predicts and prioritizes targets such as PPARγ and the aryl hydrocarbon receptor (AhR) for follow-up validation in MC3T3-E1 osteoblast differentiation studies.

Methodology:

Integrates literature and database records (STITCH, SwissTargetPrediction, PubChem) to screen active components and predict protein targets, constructs target networks and performs network pharmacology analyses with Cytoscape to refine target lists.