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An Overview of Drug Discovery
Peter W Kenny (pwk.pub.2008@gmail.com)
Some things that are hurting Pharma
• Having to exploit targets that are weakly-linked to
human disease
• Inability to predict idiosyncratic toxicity
• Inability to measure free (unbound) physiological
concentrations of drug for remote targets (e.g.
intracellular or within blood brain barrier)
Dans la merde: http://fbdd-lit.blogspot.com/2011/09/dans-la-merde.html
[𝐷𝑟𝑢𝑔 𝑿, 𝑡 ] 𝑓𝑟𝑒𝑒
𝐾 𝑑
Why is it drug discovery and not drug design?
In tissues
Free in
plasma
Bound to
plasma
protein
Dose of drug Eliminated drug
A simplified view of what happens to drugs
Drug discovery process
Lead Identification
(LI)
Target Hypothesis
Lead Optimisation
(LO)
Clinical
development
Looking for leads: An overview of screening
Chemical Space
Leads
High throughput
screening
Virtual (directed)
screening
Hit to lead
Fragment
screening
Another view of HTS
• Every assay has a dynamic range outside which the
response cannot be quantified
• Power of an assay power can be defined by weakness of
binding that can be reliably quantified
Assays
Screening and Chemical Space
Measures of Diversity & Coverage
•
• •
•
•
•
•
•
•
•
•
•
•
•
•
2-Dimensional representation of chemical space is used here to illustrate concepts of diversity
and coverage. Stars indicate compounds selected to sample this region of chemical space.
In this representation, similar compounds are close together
The neighborhood concept
The (slightly modified) Hann molecular complexity model
This model is equally relevant to conventional and fragment-based screening. See Hann, Leach
& Harper J. Chem. Inf. Comput. Sci., 2001, 41, 856-864 | http://dx.doi.org/10.1021/ci000403i
Molecular complexity
Probability P[fit]
P[detect|fit]
P[lead]
Degree of substitution as measure of molecular complexity
The prototypical benzoic acid can be accommodated at both sites and, provided that binding can be
observed, will deliver a hit against both targets See Blomberg et al JCAMD 2009, 23, 513-525 |
http://dx.doi.org/10.1007/s10822-009-9264-5 | This way of thinking about molecular complexity is
similar to the ‘needle’ concept introduced by Roche researchers. See Boehm et al J. Med. Chem.
2000, 43, 2664-2774 | http://dx.doi.org/10.1021/jm000017s
Hopkins, Groom & Alex, DDT 2004, 9, 430-431
Ligand Lipophilicity Efficiency
LLE = pIC50 - ClogP
Leeson & Springthorpe , NRDD 2007, 6, 881-890.
Measured binding is scaled Measured binding is offset
Binding Efficiency
Measures
Ligand Efficiency
LE= DGº/NonHyd
FBDD Essentials
Screen fragments
Synthetic
Elaboration
Target
Target & fragment hit
Target & lead
Link
Fragment Elaboration Tactics
Merge
Grow
• Control of properties of compounds and materials by
manipulation of molecular properties
Molecular Design
Hypothesis-Driven
Framework in which to
assemble SAR/SPR as
efficiently as possible
Prediction-Driven
Assumes existence of
predictive models with
required degree of
accuracy
Molecular Design
Molecular Recognition
• Framework for design hypotheses
• Functional behavior of molecules is determined by the
interactions of its molecules with the different
environments in which they exist
• Mutual presentation of molecular surfaces
• For association in water we need to match interaction
potential to maximise affinity
Molecular Interactions and Drug Action
-0.316
-0.315
-0.296
-0.295
Bioisosteric relationship: Carboxylic acids and tetrazoles
JCIM, 2009, 49, 1234-1244
-0.262
-0.261
-0.268
-0.268
Molecular electrostatic potential minima (Vmin; electronic units)
shown for acetate and 5-methyltetrazole anions
Cartoon representation of hydrophobic effect
Polar Surface
Binding Pocket
Cartoon representation of hydrophobic forces
Molecular
Size
Lipophilicity
Ionisation
(pKa)
Solubility
Metabolic
stability
Off-target activity
(e.g. CYPs, hERG)
Volume of
distribution
Permeability
Active
transport
Property-based design
Plasma
protein binding
Lipophilic & half ionised Hydrophilic
Introduction to partition coefficients
Octanol/Water Alkane/Water
Octanol/water is not the only partitioning system
Does octanol/water ‘see’ hydrogen bond donors?
--0.06 -0.23 -0.24
--1.01 -0.66
Sangster lab database of octanol/water partition coefficients: http://logkow.cisti.nrc.ca/logkow/index.jsp
--1.05
P
O
O
O
F F
P
O
O
O
F F
15M
Inactive at 200M
N
S
N
O
O
O
N
S
N
O
O
O
OMe
N
S
N
O
O
O
N
S
N
O
O
O
OMe
AZ10336676
3 mM
conformational lock
150 M
hydrophobic m-subst
130 M
AZ11548766
3 M
PTP1B: Fragment elaboration
Elaboration by Hybridisation: Literature SAR was mapped
onto the fragment AZ10336676 (green). Note overlay of
aromatic rings of elaborated fragment AZ11548766 (blue)
and difluorophosphonate (red). See Bioorg Med Chem Lett,
15, 2503-2507 (2005)
Effect of bioisosteric replacement
on plasma protein binding
?
Date of Analysis N DlogFu SE SD %increase
2003 7 -0.64 0.09 0.23 0
2008 12 -0.60 0.06 0.20 0
Mining PPB database for carboxylate/tetrazole pairs suggested that bioisosteric
replacement would lead to decrease in Fu so tetrazoles not synthesised.
Birch et al, BMCL 2009, 19, 850-853
Some things to think about…
• Drug discovery:
– Sampling chemical space
• Molecular design:
– Tuning interaction potential of molecules
• Free concentration of the drug is also important

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An overview of drug discovery

  • 1. An Overview of Drug Discovery Peter W Kenny (pwk.pub.2008@gmail.com)
  • 2. Some things that are hurting Pharma • Having to exploit targets that are weakly-linked to human disease • Inability to predict idiosyncratic toxicity • Inability to measure free (unbound) physiological concentrations of drug for remote targets (e.g. intracellular or within blood brain barrier) Dans la merde: http://fbdd-lit.blogspot.com/2011/09/dans-la-merde.html
  • 3. [𝐷𝑟𝑢𝑔 𝑿, 𝑡 ] 𝑓𝑟𝑒𝑒 𝐾 𝑑 Why is it drug discovery and not drug design?
  • 4. In tissues Free in plasma Bound to plasma protein Dose of drug Eliminated drug A simplified view of what happens to drugs
  • 5. Drug discovery process Lead Identification (LI) Target Hypothesis Lead Optimisation (LO) Clinical development
  • 6. Looking for leads: An overview of screening Chemical Space Leads High throughput screening Virtual (directed) screening Hit to lead Fragment screening
  • 8. • Every assay has a dynamic range outside which the response cannot be quantified • Power of an assay power can be defined by weakness of binding that can be reliably quantified Assays
  • 10. Measures of Diversity & Coverage • • • • • • • • • • • • • • • 2-Dimensional representation of chemical space is used here to illustrate concepts of diversity and coverage. Stars indicate compounds selected to sample this region of chemical space. In this representation, similar compounds are close together
  • 12. The (slightly modified) Hann molecular complexity model This model is equally relevant to conventional and fragment-based screening. See Hann, Leach & Harper J. Chem. Inf. Comput. Sci., 2001, 41, 856-864 | http://dx.doi.org/10.1021/ci000403i Molecular complexity Probability P[fit] P[detect|fit] P[lead]
  • 13. Degree of substitution as measure of molecular complexity The prototypical benzoic acid can be accommodated at both sites and, provided that binding can be observed, will deliver a hit against both targets See Blomberg et al JCAMD 2009, 23, 513-525 | http://dx.doi.org/10.1007/s10822-009-9264-5 | This way of thinking about molecular complexity is similar to the ‘needle’ concept introduced by Roche researchers. See Boehm et al J. Med. Chem. 2000, 43, 2664-2774 | http://dx.doi.org/10.1021/jm000017s
  • 14. Hopkins, Groom & Alex, DDT 2004, 9, 430-431 Ligand Lipophilicity Efficiency LLE = pIC50 - ClogP Leeson & Springthorpe , NRDD 2007, 6, 881-890. Measured binding is scaled Measured binding is offset Binding Efficiency Measures Ligand Efficiency LE= DGº/NonHyd
  • 17. • Control of properties of compounds and materials by manipulation of molecular properties Molecular Design
  • 18. Hypothesis-Driven Framework in which to assemble SAR/SPR as efficiently as possible Prediction-Driven Assumes existence of predictive models with required degree of accuracy Molecular Design
  • 19. Molecular Recognition • Framework for design hypotheses • Functional behavior of molecules is determined by the interactions of its molecules with the different environments in which they exist • Mutual presentation of molecular surfaces • For association in water we need to match interaction potential to maximise affinity
  • 21. -0.316 -0.315 -0.296 -0.295 Bioisosteric relationship: Carboxylic acids and tetrazoles JCIM, 2009, 49, 1234-1244 -0.262 -0.261 -0.268 -0.268 Molecular electrostatic potential minima (Vmin; electronic units) shown for acetate and 5-methyltetrazole anions
  • 22. Cartoon representation of hydrophobic effect Polar Surface Binding Pocket
  • 23. Cartoon representation of hydrophobic forces
  • 24. Molecular Size Lipophilicity Ionisation (pKa) Solubility Metabolic stability Off-target activity (e.g. CYPs, hERG) Volume of distribution Permeability Active transport Property-based design Plasma protein binding
  • 25. Lipophilic & half ionised Hydrophilic Introduction to partition coefficients
  • 26. Octanol/Water Alkane/Water Octanol/water is not the only partitioning system
  • 27. Does octanol/water ‘see’ hydrogen bond donors? --0.06 -0.23 -0.24 --1.01 -0.66 Sangster lab database of octanol/water partition coefficients: http://logkow.cisti.nrc.ca/logkow/index.jsp --1.05
  • 28. P O O O F F P O O O F F 15M Inactive at 200M N S N O O O N S N O O O OMe N S N O O O N S N O O O OMe AZ10336676 3 mM conformational lock 150 M hydrophobic m-subst 130 M AZ11548766 3 M PTP1B: Fragment elaboration Elaboration by Hybridisation: Literature SAR was mapped onto the fragment AZ10336676 (green). Note overlay of aromatic rings of elaborated fragment AZ11548766 (blue) and difluorophosphonate (red). See Bioorg Med Chem Lett, 15, 2503-2507 (2005)
  • 29. Effect of bioisosteric replacement on plasma protein binding ? Date of Analysis N DlogFu SE SD %increase 2003 7 -0.64 0.09 0.23 0 2008 12 -0.60 0.06 0.20 0 Mining PPB database for carboxylate/tetrazole pairs suggested that bioisosteric replacement would lead to decrease in Fu so tetrazoles not synthesised. Birch et al, BMCL 2009, 19, 850-853
  • 30. Some things to think about… • Drug discovery: – Sampling chemical space • Molecular design: – Tuning interaction potential of molecules • Free concentration of the drug is also important