Drug Design Lecture1

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    Mahmoud Salama , PhD

    Faculty of Pharmacy

    Department of Pharmaceutical ChemistryEmail: [email protected]

    Drug Design

    Lecture I

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    20

    th

    Century: Antibiotic Era

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    20

    th

    Century: NSAIDS

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    Research and Development Phases

    The whole process takes 10 -1 5 yearsCost = $ 1.3 billion

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    Research and Development Phases

    The ideal drug candidates should be:

    1- Potent2- Selective3- Physical and Metabolic stable4- Non-mutagenic5- Non- teratogenic6- Non- Toxic

    7- Patentable8- Manufacturable

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    Two Billion Dollar Lesson

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    Two Billion Dollar Lesson

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    Two Billion Dollar Lesson

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    Drug: A chemical compound with specific pharmacological activityand minimal toxicity.

    Effective Less toxic

    Highly selective

    Molecular Target: A target responsible for executing the biologicalfunctions and in case of dysfunction, this will lead to evolution of

    clinical problems.

    9

    Important Definitions

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    Receptor: A protein molecule embedded within the surface of thecellular plasma membrane receiving signals from outside the cell.

    Hit: A selected series of active compounds either synthesized or

    naturally occurred.

    Hit To Lead: Development / Optimization of the hit compoundstowards generation of the most active prominent candidate.

    Lead: An active prominent compound to enroll clinical trials.

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    Important Definitions

    Biological B

    Natural Product N

    Semi-synthetic modification to

    Natural Product ND

    Totally Synthetic S

    Totally Synthetic but with

    natural product

    pharmacophore S*

    Natural Mimic NM

    Vaccines V

    B

    15%N

    4%

    ND

    22%S

    29%

    S*

    4%

    NM

    20%

    All New Chemical Entities 1981-2010

    V

    6%

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    Drug Receptor Interaction

    Molecular Recognition:

    Recognition of the biological molecular target andinteracting with ligands (potential drug candidates),

    then visualization in three dimensional model.

    KEY LOCK MODEL INDUCED FIT MODEL

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    Natural Products Screening

    High Through output Screening

    Side Effects Screening (Pharmacovigilance)

    Serendipity

    Natural Neurotransmitters

    Computer Aided Drug Design

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    1 Finding Lead Compounds

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    Natural Materials Screening

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    Finding Lead Compounds

    Plant Origin

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    Natural Materials Screening

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    Finding Lead Compounds

    Plant Origin

    Microbiological Origin

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    High Through Output Screening (HTS)

    Side Effects Screening (Pharmacovigilance)

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    Finding Lead Compounds

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    Serendipity

    Clonidine

    Sildenafil

    Minoxidil

    Natural Neurotransmitter

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    Finding Lead Compounds

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    Computer Aided Drug Design

    Rational Drug Design via identifying molecular target

    Design of active hits based on pharmacophore

    Pharmacophore: Chemical segment of the molecule which isessential for binding with the receptor to produce Pharmacologicalactivity

    Optimization of Hit to lead compound

    Prediction of binding affinity of ligands to the molecular target priorsynthesis

    Advantages??

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    Finding Lead Compounds

    Disadvantages??

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    2 Pharmacophore Identification

    Pharmacophore: Chemical segment of the molecule which is essential forbinding with the receptor to produce Pharmacological activity

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    3 Hit Design

    The design is followed by biological and pharmacological evaluation.

    High Through Output Screening: An automated method for screening alibrary of compounds (10,000 up to 2 million compounds) biologically forgeneration of Hit compounds.

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    4 Hit to Lead Generation

    Not all Hit compounds are eligible to be drug candidates.

    Hit to Lead generation elucidates the structural activity relationship (SAR)for further optimization.

    Tyrosine Kinase Inhibitor Used for treatment of Leukemia SAR elucidates the importance of

    substituents in the meta position for activity

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    4 Hit to Lead Generation

    The biological data derived for the synthesized hits will help to elucidatemathematical model correlating between the activity and chemical

    properties (descriptors)

    Based on this mathematical model, the activity for virtual library can bepredicted prior to its synthesis, this approach is called QuantitativeStructural Activity Relationship (QSAR)

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    4 Lead Optimization

    A library of lead compounds is generated synthetically to be biologicallyevaluated for optimization and generation the most active drug candidate

    prior to the clinical trials.

    Newly approved FDA Tyrosine Kinase Inhibitor Used for treatment of Chronic Mylogenious Leukemia Newly available in the market

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    Challenges related to drug discovery