Lecture 1: Drug targets, discovery, and screening Flashcards
Natural Products
A substance produced by a living organism
e.g. caffeine, nicotine, penicillin
Secondary metabolites
are biologically active small molecules that are not required for viability but which provide a competitive advantage to the producing organism.
Pharmacognosy
“deals with natural products used as drugs of for the production and discovery of drugs”
Why do organisms make secondary metabolites?
- Defense – insecticidal/antifeedant compounds
- Offense - antimicrobials
- Competition - antifoulants
- Reproduction - pheromones
Taxol (Paclitaxel)
Isolated from bark of the Pacific yew
Used to treat breast and ovarian
cancer
Artemisinin
An antimalarial
* Isolated from the sweet wormwood
Why are natural products important?
- NPs possess enormous structural and chemical diversity that is unsurpassed by any synthetic libraries.
- NPs are evolutionarily optimised as drug-like molecules.
- The bioactivity of natural products stems from the hypothesis that
essentially all natural products have some receptor-binding activity; the
problem is to find which receptor a given natural product is binding to - A long history of traditional medicine
- Massive untapped resource
Challenges of natural products in drug discovery
- Low yields.
- Limited supply of source material.
- The Rio Convention - Convention on Biodiversity
- Complex structures precluding practical synthesis
- Taxol – only 9 labs have reported a total synthesis. ~40 steps, yield <1%
- Complex structures posing enormous difficulty for structural
modifications.
Extraction of molecules from source
- Grind up material (could be dry or wet)
- Mix with one or more solvents
- typically varying in hydrophobicity
- May include solvent partitioning steps
Fractionation of the crude extract
- Separation of extracts into less complex mixtures
Purification of individual compounds
- Chromatography – separate compounds based on
* Hydrophobicity
* Size
* Ionic interactions - Often coupled with activity assay
* Bioassay-guided fractionation
Describe the concept of bioassay-guided fractionation.
tbc
Structure determination
A chemical structure of the drug lead is required for chemical
synthesis, medicinal chemistry, structure-based design
Chemical tests
* Detects particular functional groups or classes of molecules
* Elemental analysis (ratios of different elements)
Mass spectrometry
* Exact molecular weight and formula
Nuclear Magnetic Resonance spectroscopy
* Use NMR data to determine structure
* Non-destructive and in solution
X-ray Crystallography
* Need to be able to crystallise your compound
* Provides structure and stereochemistry
Chemical Space
The “space” spanned by all possible molecules with MW<500 Da.
Vast, > 1060 (Proteins ~10390)
Biologically relevant chemical space
- Only a small fraction of chemical space
Accessible chemical space
- Only a minute fraction of chemical space
Chemogenomics
Aims to discover active and/or selective ligands for biologically related targets in a systematic way
Ideal World
* Screen all possible compounds against all possible targets.
Real World
* Screening compound classes, enriched compound collections or focused libraries against target families (e.g. GPCRs, protein kinases, proteases)
A target family approach
* Identify small molecules that interact via a specific molecular recognition mode with a target family
Privileged scaffolds
Molecular frameworks that are capable of being ligands for a diverse
range of receptors
Drug-like molecules – Lipinski’s rule of 5
- Not more than 5 hydrogen bond donors
- Not more than 10 hydrogen bond acceptors
- A molecular mass lees that 500 daltons
- An octanol/water partition coefficient log P not greater than 5
Rules are meant to be broken
* Cyclosporine – immunosuppresant
* MW = 1203 Da
* 11 H-bond acceptors
* 27% oral bioavailability
PAINS (and IMPS)
- Pan Assay Interference Compounds
- Promiscuous compounds that give false positives in biochemical
assays - substance to avoid (??)
Antagonists vs. Agonists
Agonists – bind to and activate the receptor to produce a response.
Antagonists – bind to the receptor but do not produce a response and they
block the action of the agonist
As a general rule, it is more common and easier to develop drugs that are
antagonists to receptors, or enzyme inhibitors, rather than drugs which
activate cells, i.e. agonists.
Drug Targets
Enzymes
Intracellular receptors
* cytoplasmic
* Nuclear
Cell surface receptors
* G-coupled proteins (GCPRs)
* Ion-channels
Nucleic Acid
* DNA binding cancer drugs
Microbial membranes/cell walls
Who does DDD?
Programs in Drug Discovery and Development:
* Large pharmaceutical companies (big pharma, e.g. Pfizer, AstraZeneca,
Johnson & Johnson)
* Biotech companies (e.g. Genentech)
* Smaller start-up companies (Protagonist, Spinifex)
* Universities and Research Institutes
Why Do Drug Design and Development?
- Of huge importance to society:
- Many important diseases are not adequately treated
- need for discovery
- Drugs could be more effective and free from side effects
- need for improvement
- New diseases
- ageing population, new strains of bacteria/viruses
- Limited patent life
- need for replacement
- To make money $$$
Why make drugs
MONEY and SAVES LIVES
Two major paradigms to discovery of
drugs:
- Physiology-based discovery
- Follows physiological readouts
- Compounds screened and profiled based purely on this readout
- No initial target identification/validation
Eg. natural compound discovery
e.g Taxol (paclitaxel), Anti-cancer agent (ovarian, breast, lung) - Target-based discovery
- Begins with identifying the function of a possible therapeutic target and its role in disease
- Drugs are then designed (often first in silico) on the basis of the target, using modern chemistry methods
e.g. Omeprazole – proton pump inhibitor (PPI)
Target Validation
Need to identify whether the “target” is valid for developing drugs against
Ideally:
* Clinical efficacy and safety data of existing drugs
against that target (2nd and 3rd generation drugs
are usually better)
Animal models of disease
- Inhibit target using non pharmacological methods (ie. transgenic mice)
Estimated cost and time to develop a drug:
~10 – 15 years
High throughput screening (HTS) - definition
High throughput screening (HTS) is the process by which large numbers of compounds can be tested, in an
automated fashion, for activity as inhibitors (antagonists) or activators (agonists) of a particular biological target, such as a cell surface receptor or a metabolic enzyme
High throughput screening (HTS) - goal
Identify a molecular structure (= hit) that:
– Selectively binds to and modulates the activity of a biological target (e.g., a protein) of interest (target-based) OR
– Selectively induces a desired phenotype in a cell population or organism of interest (phenotype-based)
High throughput screening (HTS) - terminology
- Library – set of compounds to be screened
- Target – protein/pathway for drug activity
- Hit – compound with a signal above threshold
- Lead – precursor of a drug
- False negative – active against target but fails to score in assay
- False positive – not active against target but scores as a hit in assay
- Hit rate – number of ‘hits’ per screen
(HTS) - workflow
- biological target
- assay development + optimisation
- primary screening + hit reconfirmation
- secondary screening
5.medicinal chemistry optimisation
HTS four sections (?)
Library
Assay
Automation
Data Analysis and Management
Compound libraries
Types of molecule:
* Small molecules
* Proteins/peptides
Formats
* Solutions
* Fragments
* Beads
Chemical space
the space spanned by all energetically stable stoichiometric combinations of electrons, atomic nuclei and topologies in molecules. Calculated to contain up to 1 x 1060 distinct molecules.
Assay design and development considerations
- Cost considerations
- Access to sufficient quantities of proteins or cells of interest
- DMSO resistance
- Dynamic range optimisation
- Miniaturisation
Assay design – biochemical vs cell-based
Biochemical assays:
* Purified protein – enzyme or receptor
+ robust, direct readout
+ easy to validate and interpret
+ tend to be faster and higher throughput
- need lots of pure protein/enzyme/substrate
- hits need to be optimised for cell
permeability, toxicity profile etc.
Cell-based assays:
* 2nd-messenger assays, reporter gene
assays, cell proliferation, high content imaging, phenotypic
+ inbuilt permeability and toxicity screening
+ provide data in cellular context
- can be expensive and complicated
- need significant quantities of cells
- phenotypic assays tend to be lower
throughput
Assay design – detection
Fluorescence
* Organic fluorophores
* Lanthanide cryptates
* Fluorescence polarisation
* FRET
* Genetically encoded fluorophores
Luminescence
* Second reporter assays
Radioactivity
* Scintillation proximity assays
Assay examples
Scintillation proximity assays (SPA)
HTRF assays
Variation of FRET
Alphascreen
Fluorescence Polarization (FP)
Surface Plasmon Resonance imaging (SPRi)
Phenotypic assays
Methods and software to:
- Store data
- Carry out statistical analyses
- Evaluate the assay parameters
- Identify false positives/negatives
- Screen for PAINS
- Deconvolute data
- Link hits to chemical structures
Data analysis and management - PAINS
PAINS – pan-assay interference compounds
PAINs fall into hundreds of chemical classes, but there are 8 main ones that should set off alarm bells if they are detected in the “hits” in drug screens
HTS – the magic triangle
Time
Costs
Quality
