Amidha Ayurveda

26/07/26

In This Article
    Network Pharmacology - Teaching Deck
    🧬

    Network Pharmacology

    Simple teaching slides for BAMS 2nd Prof

    10-slide classroom deck

    What is network pharmacology?

    Network pharmacology is a modern approach that studies how a drug or herbal medicine works through many compounds, many targets, and many pathways together.

    • - It combines pharmacology, systems biology, and bioinformatics.
    • - It studies the body as a connected biological network.
    • - It is useful for complex diseases and herbal medicines.

    Key idea

    Compound A + Compound B + Compound C
    Target proteins and genes
    Biological pathways and disease response

    Why do we need it?

    Old view

    • - One drug acts on one target.
    • - Good for simple mechanisms.
    • - Weak for diseases with many genes and pathways.

    Network view

    • - One medicine can affect many targets.
    • - Better for cancer, diabetes, inflammation, and chronic disease.
    • - Better matches multi-herb and multi-component therapy.

    Complex diseases usually involve many interacting molecules, so a network-based method can explain medicine action more realistically than a single-target model.

    Core terms students must know

    💊

    Compound

    A chemical substance present in a drug or herb.

    🎯

    Target

    A protein, gene, receptor, or enzyme affected by a compound.

    🛣️

    Pathway

    A group of biological events inside cells that control function.

    🧫

    Disease gene

    A gene linked with the disease mechanism.

    🕸️

    Network

    A map of linked compounds, targets, pathways, and diseases.

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    Validation

    Checking predictions by docking, lab work, or literature support.

    Basic workflow of a study

    1. Select medicine and disease

    Choose a drug, herb, or formulation and define the disease question.

    2. Identify active compounds

    Collect known compounds from databases or literature.

    3. Predict targets

    Find which proteins or genes may interact with those compounds.

    4. Match with disease targets

    Look for common targets between the medicine and the disease.

    5. Build network and analyze pathways

    Use software to build the network and find important nodes and pathways.

    6. Validate results

    Support the prediction by docking, experiments, or previous evidence.

    How the network is built

    Herb / Drug
    Compounds
    Example: many phytochemicals
    Predicted targets
    Common disease targets
    Intersection matters
    PPI network
    GO / KEGG pathways
    Mechanism is interpreted here

    Important software

    Cytoscape is commonly used to visualize networks and see important nodes.

    Important idea

    Targets with high connections may be key targets, but they still need validation.

    Common databases and tools

    Compound sources

    PubChem, TCMSP, HERB, ETCM, TCMID

    Disease targets

    GeneCards, OMIM, DisGeNET

    Analysis tools

    STRING, DAVID, Metascape, KEGG, Cytoscape

    In simple words: first collect compounds, then collect targets, then compare them with disease targets, and finally study pathways and protein interactions.

    Applications in pharmacology

    🌿

    Herbal medicine

    Helps explain how multi-component herbal drugs may work.

    🧪

    Drug discovery

    Can suggest new targets, new combinations, and drug repurposing.

    🩺

    Complex disease research

    Useful in cancer, metabolic disease, inflammation, and chronic disorders.

    This approach is popular in traditional medicine research because it fits the logic of multiple active compounds acting together instead of one isolated effect.

    Advantages and limitations

    Advantages

    Easy to study multi-target action95%
    Good for herbal formulas90%
    Useful for hypothesis generation92%

    Limitations

    • - Results depend on database quality.
    • - Predicted targets may be false or incomplete.
    • - Network results alone do not prove clinical efficacy.
    • - Lab validation is still important.
    📚

    Take-home points

    • 1. Network pharmacology studies medicine action as a connected system.
    • 2. It focuses on many compounds, many targets, and many pathways.
    • 3. It is very useful for complex diseases and herbal medicine research.
    • 4. Databases and software help predict targets and pathways.
    • 5. Final conclusions should be supported by experiments and critical thinking.

    Thank you

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