PTW - Rational Drug Design

Question 1

Q: What are major challenges in the drug discovery pipeline? (3)

Answer 1

• High cost, low success rate, and late-stage attrition
• Goal is to identify effective candidates early
• Reduces time and resources spent on failed drugs

Question 2

Q: What are common methods for lead discovery and drug design? (4)

Answer 2

• Biochemical assays – screen binding/activity
• Thermal stability assays – test protein stability
• QSAR – predicts drug activity using structure-activity relationship
• Computational tools – docking, MD, crystallography, NMR

Question 3

Q: What are key experimental screening methods in drug discovery? (4)

Answer 3

• Isothermal calorimetry, SPR, mass spectrometry, DSC
• Measure binding constants (Kd), ΔH, and ΔS
• Aim for high-throughput and low target use

Question 4

Q: What thermodynamic equations define drug binding affinity? (2)

Answer 4

• ΔG = −RT ln(Kd)
• ΔG = ΔH − TΔS

Question 5

Q: What are four types of molecular docking approaches? (4)

Answer 5

• Rigid-body: Fixed structures
• Flexible: Drug and/or receptor adjusts
• Induced fit: Receptor adapts to ligand
• Fully flexible: Both drug and receptor adapt – most computationally intensive

Question 5

Q: What is the purpose of molecular dynamics (MD) in drug design? (3)

Answer 5

• Simulates drug-receptor interactions over time
• Uses Newton’s Second Law to model atom motion
• Includes solvent, flexibility, and atomic detail

Question 6

Q: How can you approach binding site identification? (4)

Answer 6

• Local (use known site and adjust ligand)
• Systematic (test all regions)
• Random (generate/score conformations)
• Simulated (use MD and annealing)

Question 6

Q: What are the advantages and challenges of MD simulations? (4)

Answer 6

• Advantages: Flexibility, solvent inclusion, atom-level resolution
• Challenges: Slow binding events, can’t model electron movement, ΔG hard to calculate

Question 7

Q: What are two types of scoring functions in docking? (2)

Answer 7

• Forcefield-based: Mechanical modelling (e.g. AutoDock)
• Empirical/knowledge-based: Use experimental affinity data

Question 8

Q: How are docking and MD combined in drug discovery? (2)

Answer 8

• MD generates conformers for docking screens
• Enables virtual screening for hit prediction

Question 9

Q: When do computational methods perform best? (2)

Answer 9

• Most effective when the binding pocket is well-defined
• Less effective for cryptic/flat surfaces like protein-protein interactions

Question 10

Q: What are advantages of ligand-based NMR methods? (4)

Answer 10

• Use small target amounts, no labelling, fast data, no size limit
• E.g., Saturation Transfer Difference (STD-NMR) and TrNOE

Question 11

Q: What are advantages of target-based NMR methods? (3)

Answer 11

• Includes titration, CSP (chemical shift perturbation)
• Gives residue-specific binding info
• Best for small targets

Question 12

Q: What does STD-NMR reveal in ligand screening? (2)

Answer 12

• Protein saturation reduces ligand signal
• Can screen libraries and rank binding affinity

Question 12

Q: What is the purpose of CSP vs [ligand] plots? (1)

Answer 12

• Used to determine the dissociation constant (Kd) from NMR titrations

Question 12

Q: What are two main crystallography approaches in drug design? (2)

Answer 12

• Co-crystallisation: Drug + protein crystallised together; no solubility limit
• Soaking: Soak native crystals in drug solution; needs soluble ligand

Question 13

Q: What is fragment-based drug design, and how does it work? (3)

Answer 13

• Screen small fragments and build larger molecules
• Strategies: Linking, growing, or merging fragments
• Linked fragments double ΔH, with minimal increase in ΔS

Question 14

Q: What equations guide fragment-based design? (2)

Answer 14

• ΔG = −RT ln(Kd)
• ΔG = ΔH − TΔS → optimised by increasing enthalpy without large entropy loss

Question 15

Q: How has drug design been used to target SARS-CoV-2? (3)

Answer 15

• Immunisation targets spike protein
• Drug design targets Mpro (protease) and RdRP (RNA polymerase)
• Uses fragment-based screening and crystallography

Question 16

Q: What was the outcome of fragment screening against SARS-CoV-2 Mpro? (2)

Answer 16

• Identified 23 non-covalent and 48 covalent hits
• Informed lead optimisation for selective inhibitors

Question 17

Q: What is involved in lead optimisation from fragments? (2)

Answer 17

• Convert hits into selective, potent inhibitors
• Optimisation takes days to weeks post-screening

Question 18

Q: Summarise key methods in rational drug design. (3)

Answer 18

• Includes experimental (NMR, crystallography, calorimetry) and computational (docking, MD, QSAR) approaches
• Fragment-based design builds on small hits
• Applied in targets like SARS-CoV-2 proteases and polymerases