Medicinal chemistry meets systems biology - PowerPoint PPT Presentation

About This Presentation
Title:

Medicinal chemistry meets systems biology

Description:

Medicinal chemistry meets systems biology John Harris, cjh Consultants (Founder and consultant to BioFocus) Cutting Edge Approaches to Drug Design – PowerPoint PPT presentation

Number of Views:134
Avg rating:3.0/5.0
Slides: 27
Provided by: kbor4
Learn more at: http://www.mgms.org
Category:

less

Transcript and Presenter's Notes

Title: Medicinal chemistry meets systems biology


1
Medicinal chemistry meets systems biology
John Harris, cjh Consultants (Founder and
consultant to BioFocus)
Cutting Edge Approaches to Drug Design MGMS,
March 2009 School of Oriental and African
Studies, University of London
2
Why should drug discoverers bother about
biological networks?
  • nearly all drugs can hit more than one effector
    target in an organism
  • not all non-target effectors are off-targets,
    metabolic systems or transporters
  • accumulated genomic/proteomic/analytical
    pharmacological knowledge confirm that several
    highly efficacious drugs exert their overall
    therapeutic effect through a network of effectors
  • the output of the network determines the drug
    profile (i.e. its good points and its bad points)

3
How should they respond to the challenges of
biological networks?
  • 1970-1990 clinical success driven by
    selectivity for single targets (e.g. h2
    antagonists, AII inhibitors). Medchem is driven
    by isolated enzyme assays or analytical
    pharmacology.
  • 1990-2000 as therapeutic targets become more
    challenging, high-throughput screening, fed by
    massively combinatorial chemistry, drives
    expectations upwards BUT the same technology
    demands assay systems even less related to the
    constituted organism!
  • 2000- 2005 unmet expectations drive a much
    more focused approach to screening but compounds
    are still, essentially, optimised against single
    reductionist assays.
  • 2005- present increasing realisation that
    reductionist assays do not predict cell network
    responses primary cell screening begins to gain
    ground.

4
Many clues along the way..
  • most of the clinically effective antipsychotics
    require polypharmacological mechanisms
    (clozapine, a broad-spectrum biogenic amine
    ligand, is as effective as 5HT2a selective
    atypical antipsychotics such as olanzapine,
    ziprasidone, etc. (see Roth et al.,
    2004NatureRevDrugDiscovery353)
  • in anti-infective therapy, polypharmacology is
    common, e.g. Wellcomes Septrin (trimethoprim and
    sulfamethoxazole hitting the bacterial
    network) or various HIV therapies (NNRTIs and
    protease inhibitors)
  • more recently, one of the earliest
    clinically-successful anticancer kinase
    inhibitors, Sutent, has been shown to be one of
    the least selective across the kinome

5
(Sauer et al., Science (2007), 316, 550) "The
reductionist approach has successfully identified
most of the components and many of the
interactions but, unfortunately, offers no
convincing concepts or methods to understand how
system properties emerge...the pluralism of
causes and effects in biological networks is
better addressed by observing, through
quantitative measures, multiple components
simultaneously and by rigorous data integration
with mathematical models"
Systems Biology and Network Pharmacology are now
very well established BIOLOGICAL activities in
academia and, increasingly, in pharma and
biotech. They are driven by major technology
advances in high-content cell screening, cellular
disease modelling and data handling/knowledge
extraction.
Whither systems medchem?
6
How should the medicinal chemist respond?
  • Historically screen in a black box
    empirical SAR but high relevance and guaranteed
    efficacy
  • Contemporary screen target in isolation
    precision SAR but relevance and efficacy
    unclear
  • The compromise take secondary screening into
    the cellular context (still much scepticism about
    primary cellular screening!) really depends on
    the degree to which the cell assays reproduce the
    target disease
  • So how DO we blend the efficacy lessons of the
    past, underpinned by network pharmacology
    evidence, with modern screening and secondary
    assay technologies?
  • How much must we change our mindset? After all,
    we optimise activity and ADME/PK more or less in
    parallel these days is an extra parallel target
    or two a quantum leap?

7
Kinases show the way forward?
  • Clinically effective first generation oncology
    drugs (e.g. Sutent, Sorafenib) act at
    several/multiple target kinases and mutants
  • These earlier multiple kinase inhibitors (MKIs)
    were discovered serendipitously (see
    2006NatureReviewsDrugDisc835)
  • How do we discover and design MKIs rationally?
    (see 2010JMC1413)
  • The challenges
  • Multiple target discovery theoretical and
    analytical
  • Lead discovery cross-screening fragment
    re-assembly chemoinformatics
  • Lead optimisation
  • balance of activities into the nearly-unknown
  • balance of physicochemical properties
  • balance of off-target activities

8
It can be done!
Lapatanib designed to hit EGFR and ErbB2 in
order to cover a wider range of tumour types
(see 2005Drugs of the Future1225)
9
Target Discovery Approaches
  • In silico
  • predict therapeutically useful combination of
    targets by network modelling and simulation
  • correlate with known drug profiles, protein
    interaction fingerprints, biomarker data
  • key input from broad chemogenomic databases
    which correlate high-quality assay data and in
    vivo data (pre-clinical and clinical) with
    specific targets
  • In vitro
  • Isolated enzyme profiling is arguably too
    reductionist at best can only point to possible
    targets or pathways
  • cell lysate fishing using ligand probes is a
    better indication especially if studying
    affinities and response time-course (e.g.
    Kinaxos KinAffinity, Cellzomes BioBeadsTM
  • High-content screening in cellular disease
    models, tracking networks, not just specific
    targets
  • Counter-screening using characterised probes

10
Fesik et al. 2006Oncogene1340 Akt-co-operating
kinases
  • A-443654 was counterscreened against 768-O cells
    transfected with a kinome-wide (443 kinases 64
    orphans) siRNA library
  • Akt-dependent apoptosis and blockade of critical
    Akt signalling pathway nodes were both sensitised
    by siRNAs encoding CK3g1 and IMPK (inositol
    polyphosphate multikinase)

11
Lead Discovery Approaches
  • In general, diversity screening against multiple
    targets may be even less cost-effective that
    against single targets, and key intra-family SAR
    is unlikely to be revealed. Pre-filtering based
    on overlapping pharmacophores a better bet
  • A rational approach to MKIs is possible
  • Feasibility assessment
  • b) Focused screening library and fragment
    cross-screening

12
Ligand SAR and cross-family common site sequences
Recent evidence supports the view that, within
protein families that have a common site of
action, similar ligands tend to bind to similar
family members (see Bamborough, 2008JMC7898
Vieth, 2005DDT839) BioFocus has developed a
simple roadmap based on the common geometry of
the kinase ATP site (activated state) which
enables quick assessment of multitarget SAR
crossover feasibility
13
Feasibility assessment A dual inhibitor of
LimK1 LimK2?
14
SoftFocus library screening gave 3 scaffolds but
only two subsite-selective fragment classes
(based on homology model docking)
15
Best dual activity for these U-shaped compounds
was 12-fold (in either direction) Subsequent
report showed nanomolar dual (equipotent)
inhibition for a series of linear compounds of
general structure
16
Focused library cross-screening
  • Despite close sequences, SAR relationships for
    similar kinases remain unpredictable, especially
    where overt or more subtle differences in binding
    mode occur
  • Many organisations have built up vast datasets
    of cross-screened kinase inhibitors which can be
    mined for MKI leads
  • IPR break-out is more of a problem with this
    strategy though

17
Fragment screening and cross-screening
  • Increasingly popular approach well suited to MKI
    design
  • Fragments sample greater chemical space and
    allow identification of preferred monomers and/or
    monomers which may not be picked up when
    screening a more decorated system
  • Fragments have no pre-determined second
    vectors and are able to probe sub-sites more
    extensively
  • Compounds can be grown from common scaffolds
    or pre-determined privileged sub-site fragments
  • Larger fragments can be screened in biochemical
    assays

18
ThemePair Fragment Libraries
  • Small fragments
  • 1 component system
  • Require affinity-based techniques (HTX-ray, NMR,
    SPR)
  • ThemePair Fragment library compounds
  • 2 component systems
  • lead-like compounds, good ligand efficiency,
    solubility HC-biochemical screening or affinity
    methods
  • Traditional focused library compounds
  • 3 component systems
  • more likely to give potency in biochemical
    screens
  • less likelihood/compound of multitarget SAR

19
Addressing multi-targeting in a rational way
using designed fragment libraries such as
ThemePair Fragments
Illustrative simplistic scenario
Primary kinase target Scaffold X, sidechains a-g
Secondary kinase target Scaffold X, sidechains
e-h
Exclusion kinase target Scaffold X, Sidechains
a,c,j
Therefore, profitable SAR area for selective
multi-targeted inhibitor is scaffold X combined
with sidechains e,f and g
20
In reality, likely that similar scaffolds will
show similar SAR at the themepair fragment level
  • Favoured area of space for required hit profile
  • Can provide a menu of scaffold and
    side-chain/monomer types

21
An example BioFocus library TPF11
  • large library (ca. gt700 compounds) based on two
    cores and 9 scaffolds extensively elaborated at a
    single position so that the scaffold becomes the
    effective second variable. These compounds are
    not reported in SciFinder or by commercial
    supplier

22
  • Lead optimisation where (medchem) going gets
    tough!
  • Balance of activities into the nearly-unknown
    until more data are available from network
    biomarker and enzyme-occupancy studies, balanced
    potency is the best guess very high
    multipotency may well not be required
  • Balance of physicochemical properties tricky
    for MKIs where structural additivity tends to
    correlate with selectivity however, deliberate
    choice of overlapping pharmacophores helps
    non-oncology applications are more challenging
  • Balance of off-target activities this issue is
    no different in principle to that for so-called
    selective kinase inhibitors, of which there are
    not many. Isolated enzyme assays are, at best, an
    approximate guide to undesirable intra-family
    activities. Monitoring cellular target/s activity
    against in vitro and in vivo toxicity readouts
    are essential in lead optimisation.

23
Facilitating parallel lead optimisation
  • Parallel optimisation is the ideal
  • This is the area of greatest current medchem
    caution! Lead optimisation against more than one
    non-ADMET/PK target is somewhat foreign to
    current practice, at least outside the kinase
    area.
  • Biochemical and cellular kinase assays need to
    be run in close conjunction with each other, even
    more so than for monovalent kinase inhibitors
    HCS technologies are beginning to impact
    optimisation in this way. Cellular assays can
    also measure inhibitory mechanisms which are
    missed by current biochemical methods
  • Cross-target SARs are, by their nature, more
    complex than single-target SARs and compromises
    are generally to be expected
  • Therefore it is very important to qualify these
    SAR compromises, preferably in cellular disease
    models or even primary cells

24
In Oncology MKIs will become the norm in the
kinase inhibitor field combination therapy and
MTDs with kinase and synergising non-kinase drugs
will emerge In Inflammation Certain MKIs will
make it to clinic and safety assessments will be
very interesting. For example, Palau have DD-2, a
dual Jak3/Syk inhibitor in preclinical for
autoimmune diseases and there are unpublished
data for related approaches Whither other
complex multifaceted diseases?
25
  • Additional references
  • Network pharmacology the next paradigm in drug
    discovery, A L Hopkins, Nature Chemical Biology,
    2008, 682.
  • What does Systems Biology mean for drug
    discovery A Schrattenholz, Vukic Soskic, Current
    Medicinal Chemistry, 2008, 1520.
  • Designed Multiple Ligands. An emerging drug
    discovery paradigm Richard Morphy, Zoran
    Rankovic, J Med. Chem., 2005, 6523.
  • The physicochemical challenges of designing
    multiple ligands Richard Morphy, Zoran Rankovic,
    J Med. Chem., 2006, 4961.
  • Logic models of pathway biology, Steven
    Watterson, Stephen Marshall, Peter Ghazal, Drug
    Discovery Today, 2008, 447.
  • Can we rationally design promiscuous drugs A L
    Hopkins, J S Mason, J Overington, Current Opinion
    in Structural Biology, 2006, 127.
  • Discovery of multitarget inhibitors by combining
    molecular docking with common pharmacophore
    features D Wei, X Jiang, L Zhou, J Chen, Z Chen,
    C He, K Yang, Y Liu, J Pei, L Lai, J Med. Chem.,
    2008, 7882.
  • Selectively Nonselective Kinase Inhibition
    Striking the Right Balance R Morphy, J Med
    Chem.,.2010, 1413.

26
Acknowledgements for helpful discussions Rich
ard Morphy (Schering-Plough) Kate Hilyard,
Chris Newton (BioFocus) Ian James (Almac
Biosciences) John Overington (EMBL
Cambridge) Colin Telfer, Finbarr Murphy (Lee
Oncology)
Write a Comment
User Comments (0)
About PowerShow.com