Pharmaceutical Chemistry: Drug Discovery and Development

1.1 Definition

  • Pharmaceutical chemistry vs. medicinal chemistry (IUPAC definitions): both examine discovery, development, planning and production of pharmaceuticals with only a few distinctions.

  • Core focus: the study of pharmaceuticals and drugs used for prevention, treatment and cure of human (or animal) diseases.

  • Key activities involved:

    • Developing new drugs from conceptualisation to marketing

    • Discovery of bioactive molecules from different sources

    • Identification and interpretation of molecular structures

    • Designing and synthesising bioactive molecules

    • Understanding interactions of molecules with humans/animals

    • Studying structure–activity relationships (SAR) of molecules

    • Identifying drug lead candidates and drug development

    • Studying already existing drugs for their formulations and quality

1.2 Why learn medicinal/pharmaceutical chemistry?

  • Career pathways prepared for roles such as:

    • Pharmacist in hospitals and chemist outlets

    • Medicinal chemist in drug discovery, production and quality assurance

    • Lecturer/researcher in universities and research institutions

    • Patent agent/attorney in government regulatory institutions

  • General pharmaceutical career pathways (example resource):

    • https://www.jcu.edu.au/courses/bachelor-of-pharmacy-honours

1.3 Drug Discovery & Development Pathways

  • Selection of disease:

    • Therapeutic need

    • Economic factors (commercial opportunity)

  • Selection of drug target:

    • Receptor, enzyme, nucleic acid, etc.

  • Identification of bioassays (screening methods):

    • In vitro, in vivo

    • Validation

    • Ultra-high-throughput screening (UHTS)

  • Finding a lead compound through UHTS:

    • From natural products (plants, animals, microbes, etc.)

    • Synthetic compound libraries (real and virtual)

  • Optimization of lead compound → drug development candidate:

    • Drug–target interactions (molecular)

    • Pharmacokinetics (ADME)

  • Preclinical and clinical trials → clinical drug candidate

  • Patenting and regulatory affairs → market launch

1.4 General drug discovery pathways

  • Timeline characteristics:

    • 10–15 years to develop a drug

    • Cost billions of dollars in research and clinical trials

    • Most fail in the clinical trial stages

    • Early lead discovery is a critical step

  • Stages (condensed):

    • 1 Early drug discovery – Lead Finding

    • 2 Pre-clinical studies of drug leads

    • 3 FDA review

    • 4 Post-market studies

1.5 Drug Development Timeline

  • Investigational New Drug (IND): a request for authorisation from the US FDA to administer an investigational drug to humans

    • extINDext{IND}

  • New Drug Application (NDA): a request for authorisation from the US FDA to market a new drug product

    • extNDAext{NDA}

1.6 Development Costs and Leading Drugs

  • Development costs (in million US-$, including failures) for leading pharmaceuticals (2019) with sales (US$):

    • 1. Humira (AbbVie): Rheumatoid arthritis, sales 19.2imes10919.2 imes 10^9

    • 2. Keytruda (Merck): Cancer immunotherapy, 11.1imes10911.1 imes 10^9

    • 3. Revlimid (Celgene): Multiple myeloma, myelodysplastic syndromes, 9.7imes1099.7 imes 10^9

    • 4. Eliquis (BMS/Pfizer): Anticoagulant, 7.9imes1097.9 imes 10^9

    • 5. Opdivo (BMS/Ono Pharm): Anticancer, 7.2imes1097.2 imes 10^9

  • Observations:

    • More than 50 ext{%} of spend is on clinical development, especially Phase III

    • Safety and efficacy requirements during marketing authorization increase over time

    • Growing complexity of diseases treated

    • Pay-off threshold: 140 ext{–}230 ext{ million US-$/year} (assuming 20 years patent protection, 13 years development)

1.7 Life-Cycle of a Drug

  • Years 0–13: research & development spending

  • Year 5: IP protection filed

  • Years 14–25: monopoly sales due to IP protection

  • Years >25: Competition and generic drugs (IP protection expired)

  • Source: German Association of Research-Based Pharmaceutical Companies (VFA)

1.8 The Pharmaceutical Market

  • Global sales context:

    • Over one-third of world-wide sales (≈ 36 ext{%}) generated in the USA

  • Trends:

    • Global pharmaceutical sales increased by more than 250 ext{%} until 2011, with a recent drop

    • “Pharmerging” markets: share of big three (USA, Japan, Europe) declining

  • Source: German Association of Research-Based Pharmaceutical Companies (VFA)

1.9 Selection of Target Disease

  • Therapeutic need:

    • Severity: self-limiting vs. life-threatening

    • Current therapy: high vs. low satisfaction (e.g., hayfever vs. AIDS)

  • Drug properties:

    • Novel approaches for convenience, e.g., Viagra™ (oral) vs. Alprostadil (injection)

    • Improvement in safety, efficacy, or new mechanism of action (MoA), e.g., H2-receptor antagonists vs. proton pump inhibitors

  • Economic factors:

    • Patient numbers (common vs. rare diseases)

    • Corporate portfolio gaps, pipeline opportunities

    • Competitors’ activities (new products, MoAs)

1.10 Drug Discovery Analogue Approach

  • Identification of lead compound via (random) screening

  • Lead sources:

    • Natural products, synthesized compounds, compound databases (libraries)

  • Lead optimization:

    • Stepwise modification of structure (functional groups, shape, geometry)

  • Outcome: optimized lead as development candidate

  • Note: Lead is rarely ideal due to issues such as low activity, poor selectivity, side effects, difficult synthesis; analogue synthesis used to fine-tune interactions with target

1.11 Drug Discovery Structure (Receptor)-Based Approach

  • Receptor-based approach:

    • Detailed 3D structure of receptor (protein) known (via X-ray crystallography or NMR)

    • Identify active site to design drugs interacting with functional groups in the site

    • Crystallization of receptor–drug complex enables design of improved drugs with greater potency and selectivity

  • Mechanistic approach:

    • Biological pathways in disease stages known at molecular level

    • Drugs designed to interfere with this pathway (e.g., enzyme inhibition)

    • Lead compound often a natural substrate; lead optimization via modification of natural substrate

    • Advantage: molecular recognition provided by natural substrate

1.12 Sources of bioactive lead molecules

  • Drugs sourced from natural products or synthetic chemicals

  • Natural product sources include plants, animals, microorganisms, minerals

  • Classic examples:

    • Morphine from plant

    • Heparin from animal

    • Penicillin from microorganism

    • FeSO$_4$ from mineral

1.13 Synthesis/Screening Cycle

  • General cycle in medicinal chemistry:

    • Target molecule (TM) identified

    • Test results (structure–activity relationship) feed back into Biological Evaluation of TM candidate for development

  • Note: Visual cycle represented in slides; concept is iterative optimization and screening

1.14 Drug Binding Sites

  • Common targets are macromolecules (proteins or nucleic acids) with large molecular mass

  • Drug interacts with the macromolecular target at a binding site (a hollow or canyon on the surface)

  • Conceptual framework: lock-and-key hypothesis

1.15 Non-covalent Intermolecular Bonding

  • Types of non-covalent interactions:

    • Ionic bonds: between ionic groups A− and B+

    • Hydrogen bonds: between a hydrogen bond donor (HBD) X–H and a hydrogen bond acceptor (HBA) Y

    • Dipole–Dipole interaction: between polarised groups (δ+ and δ−)

    • Ion–Dipole interaction: between an ionic group and a dipole

1.16 Non-covalent Intermolecular Bonding (continued)

  • Additional interactions:

    • van der Waals / London dispersion interactions

    • π-interactions (edge-to-face) between aromatic rings

    • Stacking interactions involving hydrocarbon regions

    • Caused by transient fluctuations in electron density

1.17. Acid-Base Properties of Drug

  • In vivo ionisation and ADME are influenced by acid–base properties

  • Physiological pH ranges to consider:

    • Stomach: pHext(empty) ext≈1ext–1.5;extfed ext≈2ext–4pH ext{(empty)} \, ext{≈ } 1 ext{–}1.5; ext{ fed} \, ext{≈ } 2 ext{–}4

    • Intestine: pHext≈8pH ext{≈ } 8

    • Plasma: pHext≈7.4pH ext{≈ } 7.4

  • pK$_a$ threshold used to determine ionisation state

  • Acid drugs: carboxylic acids, phenols

    • At pH < pK$_a$: HA (neutral)

    • At pH > pK$_a$: A− (ionized)

  • Basic drugs: amines

    • At pH < pK$_a$: BH$^+$ (ionized)

    • At pH > pK$_a$: B (neutral)

  • Most drugs are weak acids or weak bases

1.18 Membrane Passage

  • Ionisation state affects membrane permeation:

    • Acidic drugs pass in neutral, un-ionised form as HA

    • Basic drugs pass as B (neutral) after deprotonation

  • Hydrophobic groups can compensate for ionised functional groups

  • Membrane passage can shift equilibrium (Le Châtelier’s principle), enabling slow passage of largely ionised drugs

  • Additional routes: ion channels and transport proteins

1.19 Example: Epinephrine

  • Docked into active site of adrenergic receptor

  • Interactions include hydrogen bonds

  • Functional groups:

    • Amine function: ionised (pK$_a$ = 9.16) at physiological pH (7.4)

    • Carboxyl function: ionised (pK$_a$ ≈ 3.9)

1.20 Finding a Lead

  • Optimized lead vs lead compound:

    • Optimized lead: defined chemical substance from primary in vitro screening with sufficient potential and safety (potency, selectivity, pharmacokinetics, physicochemical properties, toxicity, novelty) to progress to full development

    • Lead compound: activity exceeds a predefined statistical threshold or robust dose–response in a primary screen (in vitro)

1.21 Finding a Lead – Lead optimization concepts

  • Lead compound binding pocket: desired characteristics for better binding include

    • Better filling of pocket

    • Less flexibility

    • Better fit

    • More interactions

  • Visual representation: optimization of binding pocket interactions

1.22 Natural Products – Advantages and Disadvantages

  • Advantages:

    • Immense variety (> 290,000290{,}000 known natural products)

    • Broad structural diversity

    • Unique and complex structures; often enantiopure (chiral pool)

  • Disadvantages:

    • Limited availability (small amounts)

    • Isolation is complex; synthesis challenging

    • Structure determination can be difficult (NMR, X-ray)

    • Environmental impact (example: Taxol production requiring large numbers of Pacific yew trees)

  • Conclusion: design simpler analogues, semi-synthesis, or bioengineering approaches

1.23 Natural Products – Examples

  • Plants: Artemisia annua (sweet wormwood) – antimalarial

  • Marine organisms: Lyngbya majuscula – antitumor; Curacin A

  • Microorganisms / Fungi: Aspergillus terreus – cholesterol reducer

  • Animals: Bothrops jararaca – ACE inhibitor; Teprotide

1.24 Example of Simple analogue design – Morphine case

  • Source: seed pods of the opium poppy

  • Morphine rule (guidelines for modifying morphinan type):

    • Tertiary amine with a small alkyl substituent

    • Quaternary carbon

    • An arene/aromatic ring attached directly to the quaternary carbon

    • An ethylene (C$_2$) spacer between the quaternary carbon and tertiary amine

  • Example transformations:

    • Morphine → Morphinanes → Benzomorphanes with a series of structural changes such as removal of ether bridge, removal of OH groups, saturation/desaturation of rings

  • Illustrative designs shown: Morphine, Morphinanes, Benzomorphanes

1.25 Medicinal Folklore

  • Historical or traditional medicines used by ancient civilizations

  • Often ineffective, dangerous, or placebo effects

  • Examples listed:

    • Rhubarb root (laxative) – China

    • Sweet wormwood (antimalarial) – China

    • Willow tree (anti-inflammatory) – England

    • Ipecac root (antiprotozoal) – South America

    • Snakeroot plant (antihypertension, antipsychotic) – India

1.26 ‘Me too’ and ‘Me better’ Drugs

  • Strategy: use established drugs from competitors

  • Advantages: therapeutic effect already proven

  • Aims: modify original structure to avoid patent protection while retaining activity

  • ‘Me better’: improvement over the original drug

  • Example: antihypertensive agents based on Captopril (Bristol-Myers Squibb)

1.27 Enhancing a Side Effect

  • Strategy: exploit minor property/side-effect of existing drugs to design new compounds

  • Concept: selective optimization of side activities (SOSA)

  • Examples built around existing pharmacophores:

    • Antihypertensive side effect: anti-ED

    • Antibacterial side effect: hypoglycemia

    • Antiallergy side effect: antimalarial

1.28 Natural Ligands for Receptors

  • Natural ligands (e.g., hormones) of target receptors can serve as lead compounds

  • Advantage: known function and mechanism

  • Example: adrenaline / noradrenaline as leads for adrenergic β-agonists

1.29 Natural Substrates for Enzymes

  • Natural substrates for enzymes as lead compounds for enzyme inhibitors

  • Advantage: enzyme’s function and substrate fate are known

  • Example: HIV protease inhibitors – peptidic transition state analogs; peptide substrates resistant to peptidases (peptide isosteres); simple pentapeptide that is cleaved by peptidase

1.30 Serendipity

  • Scientific discoveries often occur by accident

  • Notable examples:

    • Cisplatin and penicillin (premier examples)

    • Mustard gas accident during WWII led to observations about cytotoxicity and potential cancer treatment

    • Nitrogen mustards as cytotoxic chemotherapy agents

1.31 Other Strategies

  • Automated methods for synthesizing large numbers of related compounds quickly (libraries)

  • Combinatorial synthesis: solid-supported synthesis

  • Parallel synthesis: miniaturized equipment (solution or solid support)

  • Structure-based design (de novo):

    • If target structure is known, use molecular modelling to identify binding sites and design matching molecules

  • If target structure is not known: model target based on related protein with known structure (in silico design)

1.32 Chemical Assessment of a Lead

  • Key considerations:

    • Structural complexity → synthesis feasibility

    • Chemically reactive groups → potential toxicity

    • Chirality → impact on activity; easier if from the chiral pool

    • Simpler structures → often desirable if achievable

    • Retrosynthesis considerations: simple disconnections

    • Access to chiral pool (e.g., L-Ala)

    • Functional groups such as sulfonic acid and oral absorption considerations

    • Complex chirality (multiple stereocenters) increases risk

    • Aldehydes: potential reactivity/toxicity

    • Amide bonds: stability (hydrolysis) concerns

    • Alkylating agents: toxicity concerns

1.33 Lipinski’s Rule of 5

  • Derived from World Drug Index (WDI) data; heuristic for oral bioavailability/basics

  • Rules (rough guidelines):

    • H-bond donors: extHBDext≤5ext{HBD} ext{ ≤ } 5

    • H-bond acceptors: extHBAext≤10ext{HBA} ext{ ≤ } 10

    • Molecular weight: MWext≤500extg/molMW ext{ ≤ } 500 ext{ g/mol}

    • Partition coefficient: extLogPext≤5ext{LogP} ext{ ≤ } 5

  • Additional note:

    • For oral and intestinal absorption: ideally extlogPextoralextaround1.35ext–1.8ext{logP}_{ ext{oral}} ext{ around } 1.35 ext{–}1.8

  • Important caveat: not quantitative or foolproof; serves as a guideline for filtering molecules

1.34 Lipinski’s Rule of 5 – Examples

  • Morphine:

    • Ac = acetyl (CH$_3$CO), $MW = 312.4$ g/mol, $ ext{LogP} = 1.3$

  • Oseltamivir:

    • Me = methyl (CH$_3$), $MW = 285.34$ g/mol, $ ext{LogP} = 0.89$

  • Enalapril:

    • Et = ethyl (C$2$H$5$), $MW = 376.48$ g/mol, $ ext{LogP} = 2.98$

  • Notes: These examples illustrate how different substituents affect MW and lipophilicity relative to Lipinski criteria