drug design Flashcards

1
Q

drug discovery pipeline

A
  • find target gene/protein/molecule
  • discover hit
  • hit to lead
  • optimise lead
  • clinical trials
  • sales
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2
Q

hit

A
  • small molecule with an effect identified biologically/computationally
    • high throughout screening
  • either purchased or belonging to a chemical library
    • no patent possibility if purchased
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3
Q

lead

A
  • chemically modified hit with enhanced effects and better ADMET
  • ideally IC50 = 1nM (μM min)
  • improved delivery and decreased toxicity
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4
Q

lead optimisation

A
  • potency (<1nM)
  • selectivity (1000 fold against related receptor)
    • prevent effects on homologues
  • solubility (<1mg/ml)
  • ADMET
  • safe and tolerable in animals
  • efficacy in animals
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5
Q

IC50

A
  • half maximal inhibitory concentration
  • concentration that has 50% inhibiton of the target
  • measure of efficacy
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6
Q

clinical trials

A
  1. establish safe dose, side effects, absorption
  2. establish efficacy and side effects
    • confirmation of 1
  3. prove efficacy
    • compare to other treatments
    • random double blind
    • against placebo or alternative
  4. regulation/monitoring phase
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7
Q

targets of drug design

A
  • identify macromolecular target
  • find IC50
  • 1000 fold improvement in IC50 to 1nM
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8
Q

ADMET

A
  • absorption
  • distribution
    • target vs off target
  • metabolism
    • conversion to metabolites
    • prodrugs/bioactivation
    • pharmacokinetics and pharmacodynamics
  • excretion
    • aim to minimise (take drug less often)
  • toxicology
    • acute and chronic
    • 2 species before humans
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9
Q

lipinskis rule of 5

A
  • MW ≤500
  • lipophily ClogP ≤5
  • ≤5 H bond donors
  • ≤10 H bond acceptors
  • distinguishes drug like molecules from non-drug like
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10
Q

extension of lipinskis rule of 5

A
  • number of atoms between 20 and 70
  • at least one OH (except psychoactive substances)
  • <8 rotatable bonds
    • reduce unfavourable entropy of free molecule becoming fixed
  • many drugs break these
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11
Q

high throughput screening

A
  • series of small molecules form library plates and tested robotically
  • 105-106 compounds at a time
  • expensive
  • up to 1 million moelcules
    • but 1 billion possible drugs predicted
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12
Q

computer based drug design

A
  • involves ligands and receptors
    • ligand = small molecule (sometimes macromolecule)
    • receptor = macromolecule/protein/nucleic acid
  • type of modelling depends on how much you know about each
  • major aim is scaffold hopping
  • based on pharmocophore
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13
Q

types of computer-based modelling for drug design

A
  • know activities of set of ligands but not receptor
    • often with membrane proteins
  • know receptor structure but not active ligand structure
  • know structure of receptor-ligand complex
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14
Q

scaffold hopping

A
  • find new molecule structurally different to something that already exists
  • can patent
  • improve efficacy and reduce side effects
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15
Q

pharmacophore

A
  • set of molecular features arranged in their relative spatial orientation repsonsible for that molecule’s interactions
    • H bond acceptors/donors
    • charged groups
    • hydrophobic regions
    • aromatic rings
  • what the target receptor recognises
  • developed by ligand scout program
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16
Q

rationale behind pharmocophore

A
  • bioisosterism
    • certain functional groups have similar properties
  • distinct functional groups can be exchanged while maintaining biological activity
  • useful in identifying structures with desired acitivity in unexplored chemical series
  • scaffold hopping
  • pharmacophore can’t be patented
17
Q

advantages of pharmacophore

A
  • add more geometric features
    • centroids, planes, angles
    • excluded volumes (not occuppied by ligand)
      • limit searching options
    • specified distances or ranges (increased flexibility)
  • underpins basis of computer-aided drug design methods