Protein-ligand docking principles MCQs With Answer

Introduction: Protein-ligand docking principles MCQs With Answer is designed for M.Pharm students to build a solid conceptual and practical understanding of molecular docking. This short quiz collection emphasizes the theoretical foundations, algorithmic strategies, scoring functions, and practical considerations such as protein and ligand preparation, flexibility, solvent and metal handling, and validation metrics. Each question focuses on core principles and common pitfalls encountered during virtual screening and structure-based drug design, helping students prepare for exams and research tasks. Answers are provided to facilitate self-assessment and deeper study. Use this resource to reinforce docking knowledge and improve critical evaluation of docking results in drug discovery projects.

Q1. What is the primary goal of protein-ligand docking in structure-based drug design?

• To predict the binding affinity rank order for a large compound library without poses
• To determine the most probable binding pose and estimate interaction strength between a ligand and a target protein
• To simulate the full thermodynamic binding pathway including all solvent molecules explicitly
• To replace experimental binding assays entirely

Correct Answer: To determine the most probable binding pose and estimate interaction strength between a ligand and a target protein

Q2. Which category of scoring functions uses physically derived terms like electrostatics and van der Waals combined with parameterized solvation to estimate binding free energy?

• Knowledge-based scoring functions
• Empirical scoring functions
• Force-field or physics-based scoring functions
• Fingerprint-based scoring functions

Correct Answer: Force-field or physics-based scoring functions

Q3. Which docking challenge is specifically addressed by flexible docking methods as opposed to rigid-body docking?

• Scoring ligand protonation states
• Accounting for protein side chain and backbone conformational changes upon ligand binding
• Handling covalent bond formation between ligand and protein
• Computing absolute binding free energies with free energy perturbation

Correct Answer: Accounting for protein side chain and backbone conformational changes upon ligand binding

Q4. In docking, what does RMSD (root mean square deviation) commonly measure?

• The diversity of chemical scaffolds in a virtual library
• The geometric difference between a predicted ligand pose and a reference (usually experimental) pose
• The difference in binding affinities predicted by two scoring functions
• The deviation of protein backbone from ideal geometry

Correct Answer: The geometric difference between a predicted ligand pose and a reference (usually experimental) pose

Q5. Which of the following is a typical weakness of empirical scoring functions?

• They require very long molecular dynamics simulations
• They rely on fitted parameters that may not generalize well to novel chemotypes
• They are purely distance-based with no energetic terms
• They cannot be used for virtual screening due to high computational cost

Correct Answer: They rely on fitted parameters that may not generalize well to novel chemotypes

Q6. What is the main role of a docking grid or map in many docking programs?

• To store ligand conformations after docking
• To discretize the protein potential field so that ligand scoring is computationally efficient
• To perform explicit solvent placement during docking
• To predict ligand pKa values

Correct Answer: To discretize the protein potential field so that ligand scoring is computationally efficient

Q7. Which sampling algorithm is commonly used to explore ligand conformations in docking and is characterized by iterative random changes and acceptance criteria based on energy?

• Genetic algorithm
• Simulated annealing
• Deterministic gradient descent
• Principal component analysis (PCA)

Correct Answer: Simulated annealing

Q8. Why is protonation state assignment of a ligand and protein important prior to docking?

• Protonation states only affect ligand solubility, not binding
• They determine formal charges, hydrogen-bond donors/acceptors and influence electrostatic interactions important for correct pose and scoring
• Docking algorithms automatically ignore protonation state effects
• It is unnecessary because scoring functions compensate for wrong protonation

Correct Answer: They determine formal charges, hydrogen-bond donors/acceptors and influence electrostatic interactions important for correct pose and scoring

Q9. Which validation metric evaluates the ability of a docking protocol to discriminate known actives from decoys in virtual screening?

• Root mean square deviation (RMSD)
• Enrichment factor or ROC-AUC
• Bond length distribution
• pKa prediction error

Correct Answer: Enrichment factor or ROC-AUC

Q10. What is consensus scoring in docking?

• Using a single scoring function but with repeated runs
• Combining rankings or scores from multiple scoring functions to reduce false positives and improve reliability
• Applying scoring only to consensus motifs in ligands
• Replacing docking scores with molecular dynamics energies

Correct Answer: Combining rankings or scores from multiple scoring functions to reduce false positives and improve reliability

Q11. In the context of docking, what is induced fit?

• The process of ligand tautomerization during binding
• The conformational adaptation of the protein active site upon ligand binding
• A rigid docking mode that fixes protein geometry
• The effect of solvent viscosity on ligand diffusion

Correct Answer: The conformational adaptation of the protein active site upon ligand binding

Q12. Which statement best describes knowledge-based scoring functions?

• They derive potentials from statistical analysis of known protein-ligand complexes
• They explicitly compute quantum mechanical energies for each pose
• They use only Lipinski’s rules as scoring criteria
• They are identical to empirical scoring functions

Correct Answer: They derive potentials from statistical analysis of known protein-ligand complexes

Q13. Which of the following is a recommended step in protein preparation before docking?

• Removing crystallographic waters in all cases without exception
• Adding missing side chains and assigning appropriate protonation states for ionizable residues near the binding site
• Leaving alternate conformations unresolved to increase sampling diversity
• Ignoring metal coordination and treating metal ions as organic atoms

Correct Answer: Adding missing side chains and assigning appropriate protonation states for ionizable residues near the binding site

Q14. When is covalent docking specifically required?

• For ligands that form a reversible non-covalent complex with the protein
• When the ligand forms a covalent bond with a specific amino acid residue during inhibition
• Only when metal ions coordinate a ligand
• For peptides exclusively

Correct Answer: When the ligand forms a covalent bond with a specific amino acid residue during inhibition

Q15. What is a common limitation of treating water molecules implicitly in docking?

• Implicit water models always increase computational cost dramatically
• They cannot represent structured or bridging water molecules that mediate key protein-ligand interactions
• Implicit models prevent ligand flexibility
• They produce exact entropic contributions from solvent

Correct Answer: They cannot represent structured or bridging water molecules that mediate key protein-ligand interactions

Q16. Which benchmark dataset is commonly used to evaluate virtual screening and docking performance?

• MNIST
• DUD-E (Directory of Useful Decoys, Enhanced)
• Protein Data Bank (PDB) as a single validation set
• ChEMBL only

Correct Answer: DUD-E (Directory of Useful Decoys, Enhanced)

Q17. What is the advantage of rescoring top docking poses with MM-GBSA?

• It is faster than the initial docking scoring and always more accurate
• It uses molecular mechanics with implicit solvation to provide a more physics-based estimate of relative binding free energies for pose ranking
• It replaces the need for experimental validation completely
• MM-GBSA only evaluates ligand conformational strain and ignores protein interactions

Correct Answer: It uses molecular mechanics with implicit solvation to provide a more physics-based estimate of relative binding free energies for pose ranking

Q18. Which parameter is most critical when defining the docking search space (box or grid center)?

• Total number of rotatable bonds in all ligands
• Location and volume that encompass the known or predicted binding site, including key residues
• The solvent model chosen for the run
• The chemical diversity of the ligand library

Correct Answer: Location and volume that encompass the known or predicted binding site, including key residues

Q19. In docking, what does enrichment factor (EF) at a given percentage measure?

• The average RMSD of top-ranked poses
• The fold-improvement in identifying actives among top-ranked compounds relative to random selection
• The number of unique scaffolds discovered
• The binding free energy difference between best and worst ranked ligands

Correct Answer: The fold-improvement in identifying actives among top-ranked compounds relative to random selection

Q20. Which feature is most indicative that a predicted docking pose might be an artifact rather than a plausible binding mode?

• The pose forms expected hydrogen bonds and hydrophobic contacts consistent with known SAR
• The ligand makes many severe steric clashes with protein heavy atoms and requires unrealistic strain to adopt the conformation
• The pose occupies the canonical pocket and aligns with known co-crystal fragments
• The top-ranked pose is consistent across independent docking runs

Correct Answer: The ligand makes many severe steric clashes with protein heavy atoms and requires unrealistic strain to adopt the conformation

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