3D-QSAR: CoMFA, CoMSIA and contour map analysis MCQs With Answer

3D-QSAR: CoMFA, CoMSIA and contour map analysis MCQs With Answer

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Introduction

3D-QSAR: CoMFA, CoMSIA and contour map analysis MCQs With Answer is a focused quiz resource designed for M.Pharm students studying MPC 203T – COMPUTER AIDED DRUG DESIGN. This set consolidates core concepts of 3D-QSAR, comparing CoMFA and CoMSIA methodologies, outlining practical modelling choices (alignment, grid, probe, charge methods), and emphasizing contour map interpretation for lead optimization. Each question highlights theoretical principles and applied best practices such as PLS validation metrics, external predictivity, and applicability domain considerations. The MCQs are designed to deepen understanding beyond basics and to train students in critically evaluating and using 3D-QSAR results in drug design workflows.

Q1. Which of the following best describes the fundamental difference between CoMFA and CoMSIA methods?

  • CoMFA uses Gaussian distance dependence for all fields while CoMSIA uses Lennard-Jones and Coulomb equations
  • CoMFA computes steric and electrostatic fields using Lennard-Jones and Coulomb potentials; CoMSIA uses Gaussian-type similarity functions and can include additional fields such as hydrophobic and hydrogen-bond donor/acceptor
  • CoMFA is a 2D-QSAR approach and CoMSIA is a 3D-QSAR approach
  • CoMFA requires no molecular alignment but CoMSIA does

Correct Answer: CoMFA computes steric and electrostatic fields using Lennard-Jones and Coulomb potentials; CoMSIA uses Gaussian-type similarity functions and can include additional fields such as hydrophobic and hydrogen-bond donor/acceptor

Q2. In a typical CoMFA study, why is molecular alignment considered the most critical step?

  • Alignment determines the number of PLS components directly
  • Alignment affects the way grid points sample the same pharmacophoric regions across molecules, directly influencing the field descriptors and model quality
  • Alignment is only important for visualization and does not change statistical outcomes
  • Alignment eliminates the need for external validation

Correct Answer: Alignment affects the way grid points sample the same pharmacophoric regions across molecules, directly influencing the field descriptors and model quality

Q3. What is the usual purpose of using Partial Least Squares (PLS) regression in CoMFA/CoMSIA analyses?

  • To perform non-linear clustering of descriptors
  • To reduce collinear high-dimensional field descriptor matrices into a few latent variables that correlate with biological activity
  • To compute molecular alignments automatically
  • To replace the need for cross-validation

Correct Answer: To reduce collinear high-dimensional field descriptor matrices into a few latent variables that correlate with biological activity

Q4. Which cross-validation metric is most commonly reported in 3D-QSAR to indicate internal predictive ability?

  • r (Pearson correlation)
  • q² (leave-one-out cross-validated correlation coefficient)
  • MAE (mean absolute error)
  • AIC (Akaike Information Criterion)

Correct Answer: q² (leave-one-out cross-validated correlation coefficient)

Q5. Typical grid spacing used for field sampling in CoMFA/CoMSIA studies is most often set to which approximate value?

  • 0.5 Å
  • 2.0 Å
  • 10.0 Å
  • 5.0 Å

Correct Answer: 2.0 Å

Q6. Why does CoMSIA avoid singularities and abrupt field changes that can be present in CoMFA?

  • Because CoMSIA uses a lower grid resolution
  • Because CoMSIA calculates fields using Gaussian-type distance weighting (smooth similarity functions) instead of point-wise Lennard-Jones/Coulomb potentials
  • Because CoMSIA removes electrostatic contributions entirely
  • Because CoMSIA uses only 2D descriptors

Correct Answer: Because CoMSIA calculates fields using Gaussian-type distance weighting (smooth similarity functions) instead of point-wise Lennard-Jones/Coulomb potentials

Q7. Which set of fields can be included in a CoMSIA analysis but not all are standard in classical CoMFA?

  • Steric and electrostatic only
  • Hydrophobic, hydrogen-bond donor, hydrogen-bond acceptor, in addition to steric and electrostatic
  • Only 2D topological indices
  • Quantum mechanical HOMO/LUMO exclusively

Correct Answer: Hydrophobic, hydrogen-bond donor, hydrogen-bond acceptor, in addition to steric and electrostatic

Q8. In contour map interpretation, what does a steric “favorable” region indicate for substituent design?

  • That reducing steric bulk in that region will increase activity
  • That adding steric bulk (larger substituents) in that region is predicted to increase activity
  • That an electronegative atom must be introduced
  • That the region should be left unchanged to maintain solubility

Correct Answer: That adding steric bulk (larger substituents) in that region is predicted to increase activity

Q9. Which probe atom and parameters are commonly specified when computing CoMFA steric and electrostatic fields?

  • A water probe with polarizability settings
  • A sp3 carbon probe (often with +1 charge for electrostatic sampling and a defined van der Waals radius)
  • A hydrogen-only probe with zero van der Waals radius
  • A heavy atom probe that ignores electrostatics

Correct Answer: A sp3 carbon probe (often with +1 charge for electrostatic sampling and a defined van der Waals radius)

Q10. What is the main reason to perform external validation (prediction on a test set) after building a CoMFA/CoMSIA model?

  • To increase q² value artificially
  • To evaluate the model’s true predictive performance on molecules not used in model training and detect overfitting
  • To avoid calculating PLS components
  • To align molecules more precisely

Correct Answer: To evaluate the model’s true predictive performance on molecules not used in model training and detect overfitting

Q11. What does a high r² but low q² imply about a 3D-QSAR model?

  • The model has excellent internal prediction and reliable external predictivity
  • The model fits the training data well (high r²) but likely overfits and has poor internal predictive ability (low q²)
  • The model requires fewer PLS components to improve performance
  • The descriptors are independent and well-balanced

Correct Answer: The model fits the training data well (high r²) but likely overfits and has poor internal predictive ability (low q²)

Q12. What is the purpose of column filtering in CoMFA/CoMSIA descriptor matrices?

  • To remove molecules with low activity
  • To eliminate near-constant or very low-variance grid column descriptors that add noise and reduce model robustness
  • To increase the number of PLS components artificially
  • To change the grid spacing dynamically

Correct Answer: To eliminate near-constant or very low-variance grid column descriptors that add noise and reduce model robustness

Q13. Which statistical technique is often used to assess whether a 3D-QSAR model may be the result of chance correlation?

  • Progressive scrambling or Y-randomization
  • Principal component clustering
  • Manual tuning of PLS components
  • Bootstrapped molecular alignment

Correct Answer: Progressive scrambling or Y-randomization

Q14. In CoMFA electrostatic maps, a region where positive charge improves activity suggests what kind of substituent should be introduced there?

  • Electron-withdrawing (negatively charged) groups
  • Electron-donating or electropositive groups that increase positive potential in that region
  • Bulky hydrophobic substituents only
  • No change; electrostatics are irrelevant

Correct Answer: Electron-donating or electropositive groups that increase positive potential in that region

Q15. Which practice improves the robustness of 3D-QSAR results when using different charge assignment methods?

  • Using arbitrary unit charges for all atoms
  • Testing multiple charge models (e.g., Gasteiger, AM1-BCC, RESP) and checking model sensitivity to the charge method
  • Ignoring electrostatics entirely
  • Setting all partial charges to zero

Correct Answer: Testing multiple charge models (e.g., Gasteiger, AM1-BCC, RESP) and checking model sensitivity to the charge method

Q16. What is the applicability domain in the context of 3D-QSAR models?

  • The range of experimental conditions used in in vitro assays
  • The chemical space and descriptor range over which the model makes reliable predictions; predictions outside this domain are less trustworthy
  • The physical laboratory where the model was developed
  • The number of PLS components included in the model

Correct Answer: The chemical space and descriptor range over which the model makes reliable predictions; predictions outside this domain are less trustworthy

Q17. When interpreting CoMSIA hydrogen-bond donor and acceptor contours, what practical guidance do they provide?

  • They indicate grid regions where adding or removing donor/acceptor functionality is predicted to increase or decrease activity, guiding functional group placement
  • They only show solvent accessibility and are not useful for substitution design
  • They indicate where to change the molecular weight of ligands exclusively
  • They replace the need for docking studies entirely

Correct Answer: They indicate grid regions where adding or removing donor/acceptor functionality is predicted to increase or decrease activity, guiding functional group placement

Q18. Which of the following is a recommended approach to select the number of PLS components in a CoMFA/CoMSIA model?

  • Choose the maximum number that yields the highest training r² irrespective of q²
  • Use cross-validation to identify the number of components that maximizes q² while avoiding overfitting confirmed by external validation
  • Always use exactly one PLS component
  • Set the number equal to the number of grid columns

Correct Answer: Use cross-validation to identify the number of components that maximizes q² while avoiding overfitting confirmed by external validation

Q19. Why might one perform region focusing or region-weighted PLS in CoMFA/CoMSIA?

  • To increase the grid spacing without losing information
  • To enhance the influence of grid regions that are more relevant to activity (improve interpretability and statistical weight of key fields)
  • To eliminate the need for alignment
  • To convert 3D fields into 2D descriptors

Correct Answer: To enhance the influence of grid regions that are more relevant to activity (improve interpretability and statistical weight of key fields)

Q20. Which diagnostic plot/method is commonly used to detect outliers or influential compounds in a 3D-QSAR training set?

  • Histogram of activity values only
  • Williams plot (plot of standardized residuals vs. leverage) to identify response outliers and structural influencers
  • Scatter plot of grid spacing vs. q²
  • Density plot of PLS component scores without considering leverage

Correct Answer: Williams plot (plot of standardized residuals vs. leverage) to identify response outliers and structural influencers

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