3D-QSAR approaches: COMSIA MCQs With Answer

3D-QSAR approaches: COMSIA MCQs With Answer

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3D-QSAR approaches: COMSIA MCQs With Answer

3D-QSAR approaches, particularly CoMSIA (Comparative Molecular Similarity Indices Analysis), link three-dimensional molecular fields to biological activity using statistical models. For B. Pharm students, mastering CoMSIA involves understanding molecular alignment, probe-based field sampling (steric, electrostatic, hydrophobic, hydrogen-bond donor and acceptor), Gaussian-type similarity functions, and descriptor matrix generation. Key analysis steps include Partial Least Squares (PLS) modeling, cross-validation (q2), r2 statistics, external validation, and contour map interpretation to guide lead optimization. Practical skills also cover dataset splitting, applicability domain, and avoiding overfitting. This concise guide emphasizes mechanistic insight and predictive reliability in drug design. Now let’s test your knowledge with 30 MCQs on this topic.

Q1. What does CoMSIA stand for in 3D-QSAR studies?

  • Comparative Molecular Similarity Indices Analysis
  • Computed Molecular Shape Interaction Analysis
  • Comparative Molecular Surface Interaction Algorithm
  • Complex Molecular Similarity and Interaction Assessment

Correct Answer: Comparative Molecular Similarity Indices Analysis

Q2. Which field types are typically included in a CoMSIA analysis?

  • Steric and electrostatic only
  • Steric, electrostatic, hydrophobic, hydrogen-bond donor and acceptor
  • Topological and 2D fingerprints only
  • Pharmacokinetic and ADMET descriptors

Correct Answer: Steric, electrostatic, hydrophobic, hydrogen-bond donor and acceptor

Q3. What mathematical function does CoMSIA use to compute similarity fields?

  • Lennard-Jones potential
  • Coulomb potential
  • Gaussian-type distance weighting function
  • Stepwise binary grid scoring

Correct Answer: Gaussian-type distance weighting function

Q4. Why is molecular alignment critical in CoMSIA-based 3D-QSAR?

  • It increases the molecular weight of compounds
  • It ensures consistent sampling of 3D fields across the dataset
  • It reduces the need for external validation
  • It replaces the need for statistical modeling

Correct Answer: It ensures consistent sampling of 3D fields across the dataset

Q5. Which statistical method is commonly used to build CoMSIA QSAR models?

  • Multiple linear regression (MLR) without dimensionality reduction
  • Partial Least Squares (PLS) regression
  • K-means clustering
  • Principal component analysis (PCA) as the final predictive model

Correct Answer: Partial Least Squares (PLS) regression

Q6. What does q2 (cross-validated r2) indicate in CoMSIA modeling?

  • The model’s external predictive power on an independent test set
  • The model’s goodness of fit to the training set only
  • The internal predictive ability estimated by cross-validation
  • The average molecular similarity score

Correct Answer: The internal predictive ability estimated by cross-validation

Q7. What does a high r2 value signify for a CoMSIA model?

  • Strong internal fit between observed and predicted activities for the training set
  • Guaranteed external predictive accuracy for any new compound
  • Low multicollinearity among descriptors
  • That no alignment was necessary

Correct Answer: Strong internal fit between observed and predicted activities for the training set

Q8. Which metric specifically assesses external predictivity of a 3D-QSAR model?

  • Internal r2 from the training set
  • Cross-validated q2 only
  • External R2 (R2pred) calculated on a test set
  • Number of PLS components

Correct Answer: External R2 (R2pred) calculated on a test set

Q9. What practical information do CoMSIA contour maps provide?

  • Optimal synthetic route for the compound
  • Regions in 3D space where modifications increase or decrease activity
  • Exact binding energy values at the active site
  • How to calculate molecular weight accurately

Correct Answer: Regions in 3D space where modifications increase or decrease activity

Q10. How does CoMSIA differ from CoMFA?

  • CoMSIA uses Gaussian similarity functions and additional fields (hydrophobic, H-bond donor/acceptor)
  • CoMSIA uses only Lennard-Jones potentials for steric fields
  • CoMSIA is a 2D-QSAR technique, while CoMFA is 3D
  • CoMSIA ignores electrostatic interactions entirely

Correct Answer: CoMSIA uses Gaussian similarity functions and additional fields (hydrophobic, H-bond donor/acceptor)

Q11. What is the typical default probe atom used to sample fields in CoMSIA?

  • An sp3 carbon probe with +1.0 charge
  • A neutral oxygen atom with -0.5 charge
  • A sodium ion probe
  • A hydrogen atom with +0.1 charge

Correct Answer: An sp3 carbon probe with +1.0 charge

Q12. What is a commonly used grid spacing for field sampling in CoMSIA studies?

  • 0.1 Å
  • 0.5 Å
  • 2.0 Å
  • 10.0 Å

Correct Answer: 2.0 Å

Q13. Why is PLS preferred over simple multiple linear regression in CoMSIA?

  • PLS requires fewer input parameters and no alignment
  • PLS handles multicollinearity and reduces many correlated variables to orthogonal components
  • PLS is a non-statistical clustering method
  • PLS eliminates the need for cross-validation

Correct Answer: PLS handles multicollinearity and reduces many correlated variables to orthogonal components

Q14. Which validation technique tests whether a CoMSIA model is due to chance correlation?

  • Leave-one-out cross-validation only
  • Y-scrambling (response permutation) test
  • Increasing the number of PLS components arbitrarily
  • Using only training set r2

Correct Answer: Y-scrambling (response permutation) test

Q15. Which practice helps to avoid overfitting in CoMSIA modeling?

  • Using as many PLS components as possible
  • Optimizing alignment with the test set included
  • Performing cross-validation and keeping an independent external test set
  • Excluding descriptor scaling and normalization

Correct Answer: Performing cross-validation and keeping an independent external test set

Q16. What does the ‘applicability domain’ of a CoMSIA model define?

  • The precise binding pose in a protein crystal structure
  • The chemical space within which model predictions are considered reliable
  • The maximum number of PLS components allowed
  • The software license limitations

Correct Answer: The chemical space within which model predictions are considered reliable

Q17. What is the purpose of bootstrapping in model evaluation?

  • To generate 3D alignments automatically
  • To assess model stability and estimate uncertainty by resampling
  • To calculate molecular docking scores
  • To determine optimal grid spacing

Correct Answer: To assess model stability and estimate uncertainty by resampling

Q18. How is the optimal number of PLS components selected in CoMSIA?

  • By choosing the number that gives the maximum training set r2 regardless of q2
  • By selecting the lowest number of components that yields an acceptable cross-validated q2 and low RMSECV
  • By always using exactly ten components
  • By using no components and raw descriptors only

Correct Answer: By selecting the lowest number of components that yields an acceptable cross-validated q2 and low RMSECV

Q19. In CoMSIA, what do the rows and columns of the descriptor matrix represent?

  • Rows are grid points; columns are atom types
  • Rows are compounds; columns are field values at grid points or derived descriptors
  • Rows are chemical reactions; columns are yields
  • Rows are PLS components; columns are cross-validation folds

Correct Answer: Rows are compounds; columns are field values at grid points or derived descriptors

Q20. Why is normalization or scaling of descriptors important in CoMSIA?

  • It increases multicollinearity intentionally
  • It equalizes descriptor variances so no field dominates due to scale differences
  • It eliminates the need for external validation
  • It converts 3D fields into 2D fingerprints

Correct Answer: It equalizes descriptor variances so no field dominates due to scale differences

Q21. Which of the following is NOT a typical step in a CoMSIA workflow?

  • Molecular alignment of congeneric compounds
  • Generation of 3D similarity fields on a grid
  • Computation of ADMET properties using in vitro assays
  • PLS model building and validation

Correct Answer: Computation of ADMET properties using in vitro assays

Q22. What is the role of an independent test set in CoMSIA studies?

  • To be used during model optimization to maximize r2
  • To provide an unbiased estimate of external predictive performance
  • To align molecules more accurately
  • To increase the number of PLS components

Correct Answer: To provide an unbiased estimate of external predictive performance

Q23. How should a student interpret a CoMSIA electrostatic contour where blue regions appear near a substituent?

  • Blue indicates a region where a more positive electrostatic potential is predicted to increase activity
  • Blue indicates hydrophobic preference only
  • Blue means steric bulk is always unfavorable
  • Blue regions are irrelevant to activity

Correct Answer: Blue indicates a region where a more positive electrostatic potential is predicted to increase activity

Q24. Why do Gaussian weighting functions used in CoMSIA offer an advantage over point-based energy sampling?

  • They create discontinuous fields that are easier to interpret
  • They avoid singularities and produce smoother, more physically meaningful similarity fields
  • They remove the need for molecular alignment altogether
  • They always yield higher r2 regardless of data quality

Correct Answer: They avoid singularities and produce smoother, more physically meaningful similarity fields

Q25. What is a commonly cited advantage of CoMSIA compared to CoMFA?

  • CoMSIA uses raw atomic coordinates without grid sampling
  • CoMSIA provides smoother similarity fields and additional interaction descriptors like hydrophobic and H-bond fields
  • CoMSIA requires no statistical validation
  • CoMSIA is a 2D method and therefore faster

Correct Answer: CoMSIA provides smoother similarity fields and additional interaction descriptors like hydrophobic and H-bond fields

Q26. What is a commonly accepted threshold for q2 (cross-validated r2) to consider a 3D-QSAR model potentially predictive?

  • q2 < 0.2
  • q2 around 0.3
  • q2 greater than 0.5
  • q2 equal to 0

Correct Answer: q2 greater than 0.5

Q27. Which r2 value is often considered indicative of a reasonable goodness-of-fit for training data in QSAR?

  • r2 less than 0.3
  • r2 between 0.4 and 0.5
  • r2 greater than 0.6
  • r2 equal to -1

Correct Answer: r2 greater than 0.6

Q28. How does PLS address multicollinearity among CoMSIA descriptors?

  • By discarding all correlated variables entirely
  • By transforming correlated descriptors into a smaller set of orthogonal latent variables
  • By increasing the dimensionality of the descriptor matrix
  • By converting 3D fields into binary flags

Correct Answer: By transforming correlated descriptors into a smaller set of orthogonal latent variables

Q29. Which of the following is NOT required as input for a CoMSIA analysis?

  • Three-dimensional structures of congeneric compounds
  • Biological activity values for the compounds
  • A defined alignment or common pharmacophore
  • High-throughput screening raw assay plate images

Correct Answer: High-throughput screening raw assay plate images

Q30. What is a primary limitation of 3D-QSAR approaches like CoMSIA?

  • They do not require experimental activity data
  • They always provide exact binding modes without docking
  • They require accurate alignment and are sensitive to the congeneric nature of the dataset
  • They can predict ADMET properties with no model building

Correct Answer: They require accurate alignment and are sensitive to the congeneric nature of the dataset

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