From screening to molecular interactions: A short tour
Peter W Kenny ([email protected])
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
Screening and Chemical Space
Measures of Diversity & Coverage
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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
Achtung!Spitfire!
Hitting the target: The old way…
Stuka on wikipedia
“Why can’t we pray for something good, like a tighter bombing pattern, for example? Couldn’t we pray for a tighter bombing pattern?” , Heller, Catch 22, 1961
…and the new
B52 on wikipedia
HTS is so glamorous…
So, Maria, why do you think it is that the
Russians are so much better than the
Germans at tennis these days?
Actually we startedto beat them at their national sport almost
70 years ago and...
.... as Uncle Joe was so fond of saying, quantity
has a quality all of its own.
… that even the stars of tennis have heard of it
• One measure of the power of an assay the weakness of
the binding that can be detected and quantified
Screening Assays
Looking for leads: An overview of screening
Chemical Space
Leads
High throughput
screeningVirtual (directed)
screening
Hit to lead
Fragment
screening
A model for molecular complexity
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
Success landscape
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
PO
O
O
FF
PO
O
O
FF
15M
Inactive at 200MN
S
N
OO
O
NS
N
OO
O
OMe
NS
N
OO
O
NS
N
OO
O
OMe
AZ103366763 mM
conformational lock
150 M
hydrophobic m-subst
130 M
AZ11548766
3 M
PTP1B: Fragment elaboration
Elaboration by Hybridisation: Literature SAR was mappedonto the fragment AZ10336676 (green). Note overlay ofaromatic rings of elaborated fragment AZ11548766 (blue)and difluorophosphonate (red). See Bioorg Med Chem Lett,15, 2503-2507 (2005)
Overview of fragment based lead discovery
Target-based compound selection
Analogues of known binders
Generic screening library
Measure
Kd or IC50
Screen
Fragments
Synthetic elaboration
of hits
SARProtein
Structures
Milestone achieved!Proceed to next
project
Why fragments?
• Access to larger chemical space
• Counter the advantage of competitors’ large
compound collections
• Ligands are assembled from proven molecular
recognition elements
• Just a smart way to do Structure-Based Design
• Control resolution at which chemical space is
sampled
• Control of properties of compounds and materials by
manipulation of molecular properties
• Prediction-Driven or Hypothesis-Driven
Molecular Design
(Descriptor-based) QSAR/QSPR:
Some questions
• How valid is methodology (especially for validation)
when distribution of compounds in training/test space
is highly non-uniform?
• Do models predict activity or just locate neighbours?
• Are ‘global’ models ensembles of local models?
• How well do the methods handle ‘activity cliffs’?
• How should we account for sizes of descriptor pools
when comparing models?
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
Molecular Interactions and Drug Action
Molecular Recognition
• 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.
Direct interactions Indirect interactions
‘Non-classical’
e.g. heavy
halogen
Electrostatic
e.g. hydrogen
bonding
Dispersion
forcesSteric clash Hydrophobic
Conformational
strain & entropy
Non-covalent interactions
A taxonomy of non-covalent interactions
Hydrogen
Bonding
Interactions between drug
molecules in crystal lattice
(Solubility, melting point
polymorphism, crystallinity)
Interactions between drug and
water molecules
(Solubility, distribution,
permeability, potency, toxicity,
efflux, metabolism)
Interactions between drug
molecules & (anti)target(s)
(Potency, toxicity, efflux ,
metabolism, distribution)
Hydrogen Bonding in Drug Discovery & Development
Interactions between water
molecules
(Hydrophobic effect)
Cartoon representation of hydrophobic effect
Polar Surface
Binding Pocket
Cartoon representation of hydrophobic forces
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
Minimised electrostatic potential has been shown to be an effective predictor of hydrogen bond basicity
Plot of V/kJmol-1 against r/Å for pyridine on lone pair axis showing electrostatic potential minimum 1.2Å from nitrogen
-300
-200
-100
0V
0 1 2 3 4 5
r
Electrostatic potential as function of position for acceptor
V/k
Jm
ol-1
r/År/Å
r
Fluorine: A weak hydrogen bond acceptor
-0.122 -0.113 -0.071
-0.038
-0.054
-0.086-0.091
-0.072
-0.104 -0.093
Hydrogen bonding of esters
Toulmin et al, J. Med. Chem. 2008, 51, 3720-3730
-0.316
-0.315
-0.296
-0.295
Bioisosteric relationship between carboxylic
acids and tetrazoles
Kenny, JCIM, 2009, 49, 1234-1244
-0.262
-0.261
-0.268
-0.268
HO
H HO
H HO
H
H
OH
N
H
O
Effect of complex formation on predicted
hydrogen bond acidity of water
1.2
(~ Alcohol)
2.0
(~ Phenol)
2.8
(~ 4-CF3Phenol)
Kenny, JCIM, 2009, 49, 1234-1244
Summary
• Screening as sampling chemical space
– Fragments are thought to allow better sampling
• Molecular design as a process of tuning
interaction potential
– Design can be hypothesis-driven or prediction-
driven