✅Lecture 1: Introduction to Drug Discovery and Protein Therapeutics - Detailed Notes

Module Information

• Assessment:

• Inverse Agonist Lab (Assessed, mandatory for learning outcomes, conducted under a Home Office License).

• Final Exam.

• Mandatory Lecture: Attendance is required for the ASPA guidelines lecture in Week 12 (Dr. Tinsley).

• Group Allocation: Will be provided.

Lecture Outline

1. General Introduction

2. The Drug Discovery and Development Path

3. Target Identification and Selection Approaches

4. Targeted Therapy in Oncology

5. Rational Drug Design and Ligandability

1. Why Current Topics in Pharmacology?

• Pharmacology is a rapidly evolving discipline.

• Current research areas at NTU include:

  • Chrono Pharmacology (how time of day affects drug action)

  • Immunopharmacology

  • Gene Therapy and Biobanks

  • Machine Learning for detection

2. Sources of Drug Leads: Natural Products

• Historical Role: Traditionally the major source of drugs and drug leads, leading to large-scale screening campaigns (e.g., ethnopharmacology, fermentation products).

• Shift in Popularity: With High-Throughput Synthesis (HTS), synthetic compound "libraries" became the main screening source, reducing the focus on natural products.

• Re-emergence: Natural products are now regaining popularity as a valuable lead source.

• Evidence: 61% of 877 small-molecule new chemical entities (1981-2002) were inspired by natural products:

  • 6% were natural products.

  • 27% were semi-synthetic derivatives.

  • 5% were synthetic compounds with natural product-derived pharmacophores.

  • 23% were natural product mimetics.

3. The Drug Discovery and Development Path

A multi-stage process often described as "Bench to Bedside":

• Target Discovery: Identification and selection of a biological target.

• Lead Discovery:

  • Assay Development

  • Lead Identification

• Lead Optimisation

• Pre-clinical Evaluation: Includes determining the first regulatory toxicity dose.

• Clinical Evaluation: Testing in humans.

4. What is a Drug Target?

• Defined as any molecule associated with a disease that can be modified by a drug to produce a therapeutic effect.

Drug Discovery Processes

• Target Identification: Finding a target with a strong, validated link to a disease is critical.

• Target Validation: The key goal is to identify a tool molecule or develop assays to support the hypothesis that modulating the target will affect the disease.

• Overall Aims of discovery projects can include:

  • First-in-class drugs

  • Biosimilars

  • Drug Repurposing

5. How Drugs Work: Modifying Targets

• Catalytic Receptors: Function as enzymes (e.g., Tyrosine Kinase, Serine/Threonine Kinase).

• Agonists: Activate receptors, increasing intracellular signalling and gene expression.

• Enzyme Inhibition:

  • Inhibitors bind to the enzyme's active site, competing with the natural substrate.

  • Most inhibitors form weak bonds, meaning they need to be administered in higher doses to remain effective by continuously occupying the active site.

6. Drug Target Space

• The human genome has ~20,000-25,000 protein-encoding genes.

• The "Druggable Genome" (genes encoding proteins that can bind drug-like molecules) is estimated to be ~3,000 genes.

• Key protein families in the druggable genome:

  • G-Protein-Coupled Receptors (GPCRs)

  • Ion Channels

  • Protein Kinases

• Current therapies address over 130 molecular targets.

• Enzymes are the largest target class for FDA-approved drugs (~27%), with non-kinase enzymes being particularly prominent.

• Distribution of Therapies: Protein therapeutics (2011-2016) are distributed across many therapeutic areas, with oncology being a major focus.

7. Rational Drug Design & Ligandability

• Molecular Recognition: Based on the "Lock and Key" (rigid) and "Induced Fit" (flexible) principles for receptor-ligand binding.

• Ligandability: The ability of a target to bind small, drug-like molecules with high affinity. This is a key assessment criterion.

8. Protein Target Assessment & Selection

• Public Resources & Databases: Used to find gene information, residue annotations, and protein structures (e.g., CANSAR, UNIPROT).

• Structure-Based Assessment: Analyzing the protein's 3D structure, function, and regulation to assess its potential as a drug target.

  • Some target classes (e.g., kinases) are well-characterized, while others (e.g., GPCRs) are less so.

• Drug Discovery Precedence: Learning from previous attempts to target similar proteins.

9. Case Study: Targeting CNOT7

• Rationale: The Ccr4-Not complex, where CNOT7 is a subunit, is a main deadenylase enzyme. It is implicated in bone formation, fertility, obesity, heart disease, and cancer metastasis.

• Hypothesis: Inhibiting CNOT7 could:

  • Prevent cancer metastasis (as high CNOT7 activity promotes it).

  • Promote bone repair/osteoporosis treatment (as CNOT7 represses bone formation).

• Challenge: CNOT7 is a non-conventional target (an Mg²⁺-dependent ribonuclease).

• Strategy: Discovery of N-hydroxyimide compounds that can chelate Mg²⁺ at the active site, inspired by inhibitors of similar enzymes (e.g., FEN-1, Influenza PA endonuclease).

10. Screening & Optimisation

• Virtual Screening: Using computational models to screen large libraries of compounds. Challenges include accounting for receptor flexibility and low success rates.

• Optimised Path to Drug Candidate: A multi-step process involving:

  • Synthesis of analogs.

  • Testing in biochemical and cell-based assays.

  • Counter-screens to ensure specificity.

  • Obtaining PK/ADME (Pharmacokinetics/Absorption, Distribution, Metabolism, Excretion) and toxicology data in preclinical species.

• Screening Approaches:

  • Phenotypic Screening: Observing the effect of a compound in cells or tissues without a predefined target.

  • Target-Based Screening: Screening against a specific, known target.

    • Includes Fragment-Based Drug Design, Structure-Guided Drug Design, and DNA-Encoded Libraries (DELs).

11. Drug Repurposing

• Definition: Investigating existing drugs for new therapeutic indications.

• Aims:

  • Accelerate development by skipping early phases.

  • Address unmet medical needs (e.g., rare diseases).

  • Reduce development costs.

• Examples of Success:

  1. Minoxidil: Anti-hypertensive → Hair loss treatment.

  2. Imatinib: CML (BCR-ABL inhibitor) → Gastrointestinal stromal tumours (KIT inhibitor).

  3. Sildenafil (Viagra): Angina/Hypertension → Erectile dysfunction.

  4. Thalidomide: Morning sickness → Multiple myeloma.

  5. Sorafenib, Azacitidine, Decitabine: Failed for one cancer → Approved for others.

  6. Dexamethasone: Various inflammatory conditions → COVID-19 treatment.

• How it's Done:

  • Genomics: Using databases like DisGeNET and COSMIC to find new gene-disease links.

  • Structural Approaches:

    • Molecular Docking: Modeling drug-target binding.

    • Inverse Docking: Docking a single drug against multiple protein targets to find new interactions. Uses databases (ChemSpider, PDB) and prediction tools like AlphaFold.

  • Biochemical/Cell-Based Approaches: Using High-Throughput Screening (HTS) data from resources like ChEMBL to profile drug activity.

• Challenges:

  • Scrutinizing differences between original and new indications.

  • Re-evaluating safety, PK/PD properties, and potential need for new formulations/dosing.

  • Managing drug combinations and interactions.

12. Summary of Key Points

• Target identification and validation are foundational to drug discovery.

• Proteins, especially enzymes, are key therapeutic targets due to their role in disease.

• Drug repurposing is a growing, efficient strategy for developing new treatments.

• The discovery process involves generating pure lead compounds and developing validated assays to test them.

• Screening can be phenotypic (effect-based) or target-based (mechanism-based).

13. Key Question for Consideration

"Imagine you are part of a research team tasked with repurposing an existing drug for a newly emerging disease. What scientific, ethical, and economic factors would you need to consider before proposing the drug for clinical trials? Can you think of a real-world example where drug repurposing significantly impacted public health?"

• Scientific: Mechanism of action, PK/PD, dosage, safety profile for the new disease.

• Ethical: Informed consent, urgency, equitable access.

• Economic: Cost-effectiveness, manufacturing scale-up, intellectual property.

• Real-world example: Dexamethasone for COVID-19.

14. Resources for Further Reading

• Key textbooks: Pharmacology by Rang & Dale; FASTtrack Pharmacology.

• Key articles on:

  • Recent advances in protein target identification (ScienceDirect).

  • Therapeutic protein development (Lagassé et al.).

  • Computational drug repurposing (Ziaurrehman-Tanoli et al.).

  • Drug discovery by repurposing (Gupta et al.).

• Guided Independent Reading: Molecular Pharmacology: From DNA to Drug Discovery (Chapter 3).

Recommended read info:

1. Rang & Dale’s Pharmacology (8th Ed.) — Core Exam Material 

General Principles

• Pharmacodynamics

  • Targets: receptors (GPCRs, ion channels, enzymes, transporters).

  • Concepts: affinity, efficacy, potency, full vs partial agonists, competitive vs non-competitive antagonists, inverse agonists, allosteric modulators.

  • Dose-response curves.

• Pharmacokinetics (ADME)

  • Absorption: oral vs parenteral, first-pass effect.

  • Distribution: plasma protein binding, Vd.

  • Metabolism: phase I (CYP450 oxidation/reduction), phase II (conjugation).

  • Elimination: renal clearance, half-life (t½), clearance (Cl).

  • Clinical importance: dosing schedules, interactions.

• Molecular & Cellular Aspects

  • Signal transduction: cAMP/PKA, IP3/DAG, MAPK cascade, JAK-STAT.

  • Desensitization & receptor regulation.

  • Electrophysiology of ion channels → basis for anaesthetics, anticonvulsants, antiarrhythmics.

• Cellular outcomes: proliferation, apoptosis → exploited in anticancer therapy.

Chemical Mediators

• Cholinergic transmission:

  • Receptors: M1–M5, Nm, Nn.

  • Drugs: muscarinic agonists/antagonists, anticholinesterases, neuromuscular blockers.

• Noradrenergic transmission:

  • α1 (vasoconstriction), α2 (presynaptic inhibition), β1 (heart), β2 (bronchi/uterus), β3 (lipolysis).

  • Drugs: α/β agonists & antagonists, clinical uses (HTN, asthma, arrhythmias).

• 5-HT (Serotonin):

  • 5-HT1 (triptans for migraine), 5-HT2 (hallucinogens, antipsychotics), 5-HT3 (antiemetics), 5-HT reuptake transporters (SSRIs).

• Histamine:

  • H1 (allergy; antihistamines), H2 (acid secretion; ranitidine), H3 (CNS), H4 (immune).

• Cytokines & biologicals:

  • TNFα inhibitors (infliximab, etanercept), IL-6 inhibitors (tocilizumab).

  • Used in RA, IBD, cancer immunotherapy.

Organ Systems

• CV Drugs:

  • Antihypertensives: ACEi, ARBs, β-blockers, CCBs, diuretics.

  • Heart failure: diuretics, ACEi, ARBs, β-blockers, aldosterone antagonists.

  • Arrhythmias: Class I–IV antiarrhythmics (Na, β, K, Ca channel blockers).

  • Ischaemic heart disease: nitrates, β-blockers, CCBs.

• Respiratory: β2 agonists, muscarinic antagonists, corticosteroids, leukotriene antagonists.

• Renal: diuretics (loop, thiazide, K-sparing, osmotic).

• Endocrine:

  • Diabetes: insulin, metformin (AMPK activation), sulfonylureas, SGLT2 inhibitors.

  • Thyroid: levothyroxine, carbimazole.

Nervous System

• Neurodegenerative:

  • Alzheimer’s: cholinesterase inhibitors (donepezil), NMDA antagonists (memantine).

  • Parkinson’s: levodopa + carbidopa, dopamine agonists (pramipexole), MAO-B inhibitors (selegiline).

• Psychiatry:

  • Anxiety: benzodiazepines (GABA_A), buspirone (5-HT1A).

  • Depression: SSRIs, SNRIs, TCAs, MAOIs.

  • Psychosis: typical (D2 blockers), atypical (5-HT2A + D2).

• Pain: opioids (μ, κ, δ receptors), NSAIDs (COX inhibition), paracetamol.

Infection & Cancer

• Antibiotics:

  • Cell wall: β-lactams, vancomycin.

  • Protein synthesis: tetracyclines, macrolides, aminoglycosides.

  • DNA/RNA: fluoroquinolones, rifampicin.

• Antivirals: acyclovir, HAART.

• Antifungals: azoles, amphotericin B.

• Cancer drugs: alkylating agents, antimetabolites, taxanes, kinase inhibitors, mAbs.

2. FASTtrack Pharmacology (2nd Ed.) — Exam Essentials

• PD & PK: clear, simple bullet points on receptors, agonists, antagonists, dose-response, clearance, t½.

• Nervous system: focused tables of anxiolytics, antidepressants, antipsychotics, anticonvulsants, anaesthetics.

• Cardio/Respiratory/Renal: drug classes with uses + key adverse effects.

• Chemotherapy: antibiotic MoAs, resistance, cytotoxic vs targeted anticancer.

• Miscellaneous: anticoagulants, NSAIDs, DMARDs, skin drugs.

3. Molecular Pharmacology (Ch.3) — Exam-Relevant Concepts

• Target identification: compare gene/protein expression in health vs disease.

• Functional genomics:

  • CRISPR, RNAi, antisense → knockout/knockdown → phenotype = validates target.

• Recombinant DNA: expression of human/mutant proteins in host cells for HTS or disease modelling.

• Signalling pathways: MAPK (cancer), JAK-STAT (inflammation), PI3K-AKT-mTOR.

• Drug resistance: mutations in target, activation of bypass pathways.

• Assays:

  • Target-based (biochemical binding).

  • Phenotypic (cell proliferation, apoptosis, Ca²⁺ flux).

Key takeaway: drugs act on networks, not isolated proteins → examiners love this phrase.

4. Key Articles — High-Yield Takeaways

• Lagassé et al. (Therapeutic proteins)

  • Classes: mAbs, Fc-fusions, ADCs, bispecifics, enzymes.

  • Pros: high specificity, tackle “undruggable” targets.

  • Cons: expensive, immunogenicity, delivery issues.

• Ziaurrehman-Tanoli et al. (Computational repurposing)

  • Signature-based (LINCS), target-based (docking), network-based (PPI).

  • Databases: ChEMBL, DrugBank, DisGeNET, SIDER.

  • Always requires experimental validation.

• Gupta et al. (Cancer repurposing)

  • Categories: anti-inflammatories (NSAIDs), metabolic (metformin), psychiatric (antipsychotics), anti-infectives (doxycycline).

  • Advantage: faster clinical translation due to known safety.

  • Challenge: off-patent → IP/funding problems.

• Protein target ID (ScienceDirect reviews)

  • Techniques: CETSA, TPP, DARTS, affinity capture, chemical proteomics.

  • Used to match phenotypic hits → molecular targets.