Choose a target and find hit/lead compounds I Flashcards

1
Q

Choosing a target compound

A
  • Requirement for a new drug
  • Economic factor
  • Understand the macromolecules involved in drug target
  • Targeting specific species e.g antiviral
  • Target specific to body or tissues
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2
Q

Target validation

A
  • Confirm association with disease proton interaction and signalling pathways
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3
Q

In-vitro

A
  • Specific to tissue cells and enzymes
  • Use bacteria and yeast to produce enzymes IC50 wich are competitive or non competitive
  • Receptor agonist or antagonist can be tested on isolectic tissue has target receptor on surface
  • pK properties - metabolism of drug
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4
Q

In-vivo

A
  • Introduce clinical condition in animals
  • Trangenic animal has some human tissue in animal
  • Slow and expensive with animal symptoms
  • Could be caused due to physiology
  • Invalid results sometimes
  • Variable according to species
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5
Q

High-throughput screening

A
  • Automated test of a large number of compounds to a large number of targets to HIT identification
  • False positive HITS can occour
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6
Q

Screening NMR

A
  • Detects whether the proton binds to the proton target the screen mixture tests 1000 molecules a day
  • Detection of eeak binding so there is no false positive
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7
Q

Process of screening NMR

A
  • NMR of the drug is taken
  • Protien is added and spectrum is re-run
  • If drug didn’t bind then NMR spectrum will be detected
  • Drug binding then no NMR spectrum will be detected
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8
Q

Isothermal calorimetry

A
  • Determine the thermodynamic between drug and its protein target
  • Can see its binding affinity and enthalpy change
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9
Q

Finding HIT compound

Screening natural compounds

A
  • Active on compound with low cytotoxicity
  • Active principle metabolites are extracted fractionate and isolate
  • Plant source - Morphine, Cocaine, Taxol
  • Microorganism - Bacteria fungi
  • Marine sources - coral, sponges and fishes
  • Animal sources - Anti venom and toxin
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10
Q

Finding HIT compound

Screening synthetic compound libraries

A
  • Compound or synthetic ingreedient that has been previously synthesised
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11
Q

Finding HIT compound

Existing drugs

A
  • Use estabilished drugs from competitors as HIT compound to design compound to modify the structure
  • Avoid patient restrictions, retains activity and has better theraputic effect
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12
Q

Selective optimisation of side effects activities

A
  • Enhance the desired effect and eliminate major biological activity of existing drugs
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13
Q

Repurposing

A
  • Screen existing compounds that are either in use in clinical or have reached late clinical stage againt a new target
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14
Q

Starting from natural ligand or modulator

Natural ligand

A
  • Used as a HIT agonist (adrenaline) for the design of an antagonist (histamine)
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15
Q

Starting from natural ligand or modulator

Natural substrates for enzymes

A
  • Used as HIT design inhibitors HIV protease enabled development of HIV protease inhibitor
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16
Q

Starting from natural ligand or modulator

Ezyme products as HIT compounds

A
  • Use HIT to design inhibitors such as carboxypeptidase
17
Q

Starting from natural ligand or modulator

Natural modulators as HIT compounds

A
  • Receptor enzymes are under allosteric control
  • Natural chemicalexert control on mudulators serving as HIT compounds
18
Q

Finding HIT compound

Serendipity

A
  • Found by chance
  • Unexpected and benificial spin-offs - lipophilic can cross blood brsin barrier add hydrophobic amide - practonol fewer side effect
  • Reaserch from different field
19
Q

Finding HIT compund

Computer aided design

A
  • Stuudy the 3D stucture on the computer
  • X-ray crystallography
  • Target analysis - rationally design a target to bind
  • Easier if co-crystallised ligand where binding site is known
20
Q

HIV protease inhibitor

A
  • Active as a homodimer for viral replication forms the active version of viral non-structure protiens
21
Q

What is target analysis?

A
  • Residue from active binding site analysed to identify key interactions to design new ligand inhibtors
22
Q

Intermolecular bonding forces
Strong to weak

A

-Ionic
- Hydrophobic
- Hydrogen - donor or acceptor
- Pi bonding
- Weak hydrogen bond
- Vderwaals and induced dipole

23
Q

HIV potent inhibitors

A
  • HAART drugs such as saquinavir and nelfinavir
  • Nelfinavir non-peptidic inhibitor occupies active site smaller and compact improved fit to hydrophobic region
24
Q

Pharmacophores modelling

A
  • Extract information on essential functional groups and 3D spatial arrangement required for activity on a given target
  • Shows binding groups for essential activity design new mordels or improve existting
25
Q

Virtual screening

A
  • Computer simulations which predicts if the compund is good or not for binding
  • Faster, easier, cheaper and safter - forms virtual HITs
26
Q

Structural based virtual screening

A
  • Molecular docking virtual compound explore its possible conformations
  • Identify best predicable binding
  • Ranks generated pose scoring predict free energy change when binding
  • interaction + association + conformation + Rotation + vibration + solvation = Free energy bind
27
Q

Ligand based virtual screening

A
  • Shape similarites with know active molecules - Shape functional group matching with query molecule
  • Higher HIT rates
28
Q

Mixed virtual screening

A
  • Matching pharmacophoric query fitting to given model
29
Q

Exclusion volumes

A
  • Added to mixed screening to show actual volume occupied avoid selecting molecules that can clash to the target
30
Q

Fragment base HIT discovery

A
  • Small molecule fragments are screened against a given target binding weakly
  • Once multiple fragments are identified the crystal structure is resolved linking fragments together optimised high affinity molecule
31
Q

Linking fragments

A
  • Bigger molecules with good affinity futher optimisation occours
32
Q

What fragments should be used in screening

A
  • Relative molecular mass <300 and >150
  • H-bond donating groups 3 or less
  • H-bond accepting groups 3 or less
  • Log(P) 3 or less
  • Number of rotatable bonds 3 or less
33
Q

What fragments should be used in screening

A
  • Relative molecular mass <300 and >150
  • H-bond donating groups 3 or less
  • H-bond accepting groups 3 or less
  • Log(P) 3 or less
  • Number of rotatable bonds 3 or less
34
Q

SAR by NMR epitope mapping

A
  • Screen small fragment then combing them to a potent HIT using NMR
  • Shifts seen on protien amide signals motier if and where binding takes place
  • Repeat to find small ligand binding sub-region then optimised