DK - Small Molecule Drug Discovery II

Question 1

Q1: What are the four main strategies used in modern drug design? (4)

Answer 1

1. Structure-Based Design – Designing drugs based on the 3D structure of the target protein.
2. Kinetic Design – Optimizing binding kinetics (on-rate/off-rate) between drug and target.
3. High Throughput Screening (HTS) – Experimentally testing large libraries of compounds for activity.
4. In Silico Design / AI-Based Design – Using computational models and machine learning to predict active compounds.

Question 2

Q2: What is structure-based drug design and what tools are used? (5)

Answer 2

• SBDD uses the 3D structure of a protein to guide molecule development.
• Pioneered in the 1990s (e.g., by Vertex).
• Involves analyzing the active site and how ligands fit.

Tools include:

• Linker design
• Scaffold hopping
• Fragment growing
• Pattern replacement
• Computational models are followed by experimental validation using assays.

Question 3

Q3: What is SAR and how is it used in structure-based drug design? (4)

Answer 3

• Structure–Activity Relationship (SAR) maps how changes in chemical structure affect drug activity.
• Helps identify regions to modify or preserve in the molecule.
• Visualization: yellow = “modify”, purple = “keep”.
• Automated techniques improve binding, solubility, and efficacy.

Question 4

Q4: What are essential steps in evaluating a protein target for structure-based design? (5)

Answer 4

• Obtain high-resolution 3D structure of the protein.
• Identify the active site and determine how it contributes to mechanism of action (MOA).
• Consider active site dynamics – is it rigid or flexible?
• Perform ligand-receptor fit analysis to evaluate binding conformations.
• Use this information to design new leads with enhanced fit and activity.

Question 5

Q5: How does kinetic drug design assess compound binding? (6)

Answer 5

• Based on binding kinetics rather than just affinity.
• Uses Surface Plasmon Resonance (SPR) to measure interaction in real time.

Steps:

1. Compound library is flowed over a sensor chip with immobilized protein.
2. Binding events cause changes in light reflection, measured by a detector.
3. SPR data shows on-rate (kon) and off-rate (koff).

• Can also analyze protein–protein interactions similarly.
• Helps identify tight-binding or long-lasting compounds.
• SPR enables precise real-time kinetic data for decision-making.

Question 6

Q6: What is HTS and how is it applied in drug discovery? (5)

Answer 6

• Screens large compound libraries against biological targets.
• Uses multiwell plates with cells or biochemical assays.

Steps:

1. Cell seeding in plates.
2. Add small molecules from the library.
3. Apply fluorescent stains or markers.
4. Use automated imaging to record outcomes.

• Produces “hits” for further profiling of potency, selectivity, toxicity, and mechanism.

Question 7

Q7: What is in silico drug design and what makes it powerful? (6)

Answer 7

• Uses AI/ML models trained on large databases to predict drug–target interactions.
• Models use input from:
  • Protein structure databases (e.g., PDB, ePDB)
  • Chemical libraries (e.g., PubChem, ChemSpider, ZINC)

Process:

1. Train ML models on bioactivity, chemical, and structural data.
2. Perform virtual screening to rank compounds by predicted affinity, ADMET, or selectivity.
3. Use molecular docking software (e.g., Autodock-Vina, Glide, Gold).
4. Apply molecular dynamics simulations (e.g., AMBER, GROMACS) to refine predictions.
5. Perform hit optimization – suggest modifications (e.g., add a methyl group) to improve potency or reduce off-target effects.