Hansch analysis – principles and application MCQs With Answer

Hansch analysis – principles and application MCQs With Answer

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In Hansch analysis, a classical QSAR approach, relationships between chemical structure and biological activity are quantified using physicochemical descriptors like lipophilicity (log P, Hansch π), electronic (Hammett σ) and steric (Taft Es) parameters. B.Pharm students learn to construct Hansch equations using multiple regression, interpret coefficients (including parabolic π2 terms), assess model quality with r2, F-test and cross-validation (q2), and understand applicability domain and limitations. Applications include lead optimization, SAR interpretation, and early ADME prediction. Key skills: descriptor selection, multicollinearity handling, model validation and rationalizing substituent effects on potency. Now let’s test your knowledge with 30 MCQs on this topic.

Q1. What is the primary goal of Hansch analysis in medicinal chemistry?

  • To model protein-ligand docking poses
  • To correlate chemical substituent descriptors with biological activity
  • To design 3D pharmacophores from active compounds
  • To predict metabolic pathways using enzyme kinetics

Correct Answer: To correlate chemical substituent descriptors with biological activity

Q2. Which of the following is NOT a common descriptor used in Hansch analysis?

  • Lipophilicity (Hansch π / log P)
  • Hammett electronic constant (σ)
  • Taft steric constant (Es)
  • Protein binding free energy from molecular docking

Correct Answer: Protein binding free energy from molecular docking

Q3. Which equation form best describes a typical Hansch model?

  • Biological activity = function of 3D molecular fields only
  • Biological activity = k0 + k1π + k2π^2 + k3σ + k4Es (multiple regression)
  • Biological activity = sequence alignment score
  • Biological activity = sum of docking scores across proteins

Correct Answer: Biological activity = k0 + k1π + k2π^2 + k3σ + k4Es (multiple regression)

Q4. What does the Hansch π (pi) value represent?

  • The substituent’s contribution to molecular refractivity
  • The substituent’s contribution to lipophilicity (log P)
  • The substituent’s steric bulk measured in Å
  • The substituent’s ionization constant (pKa)

Correct Answer: The substituent’s contribution to lipophilicity (log P)

Q5. The Hammett σ constant is used to describe which property of a substituent?

  • Hydrophobic surface area
  • Electron-withdrawing or -donating electronic effects
  • Stereochemical orientation in 3D space
  • Rate of microsomal clearance

Correct Answer: Electron-withdrawing or -donating electronic effects

Q6. Taft Es is primarily a measure of:

  • Electronic resonance effects
  • Steric hindrance or size of a substituent
  • Lipophilicity relative to benzene
  • Hydrogen bond donor capacity

Correct Answer: Steric hindrance or size of a substituent

Q7. If the coefficient of π in a Hansch equation is positive, what does it imply?

  • Activity decreases as lipophilicity increases
  • Activity increases as lipophilicity increases
  • Lipophilicity has no effect on activity
  • The descriptor π is incorrectly calculated

Correct Answer: Activity increases as lipophilicity increases

Q8. Inclusion of a π^2 (parabolic) term in a Hansch model indicates:

  • Linear increase of activity with lipophilicity
  • That lipophilicity is irrelevant to activity
  • A non-linear relationship with an optimal lipophilicity
  • That electronic effects are dominating

Correct Answer: A non-linear relationship with an optimal lipophilicity

Q9. In QSAR validation, q2 commonly refers to:

  • The squared correlation coefficient of the training set (r2)
  • The cross-validated correlation coefficient (leave-one-out or other)
  • The quantum mechanical energy of the molecule
  • The squared error of docking predictions

Correct Answer: The cross-validated correlation coefficient (leave-one-out or other)

Q10. Which transformation of activity data is often used in Hansch analysis for enzyme inhibitors?

  • Raw IC50 values in micromolar
  • Log(1/IC50) or pIC50 (negative log of IC50)
  • Percent inhibition at a single concentration
  • Area under the curve (AUC) from pharmacokinetics

Correct Answer: Log(1/IC50) or pIC50 (negative log of IC50)

Q11. How is multicollinearity among descriptors in a Hansch model typically detected?

  • By calculating variance inflation factor (VIF)
  • By measuring molecular weight only
  • By computing docking scores
  • By counting the number of hydrogen bond donors

Correct Answer: By calculating variance inflation factor (VIF)

Q12. The applicability domain of a Hansch model refers to:

  • The set of software packages that can run the model
  • The chemical space (structural and descriptor range) where predictions are reliable
  • The time window during which data were collected
  • The range of biological assays that measure toxicity

Correct Answer: The chemical space (structural and descriptor range) where predictions are reliable

Q13. A major limitation of classical Hansch analysis is:

  • It requires 3D alignment of molecules
  • It only works for peptides
  • It often requires a homologous series of structurally related compounds
  • It cannot use lipophilicity as a descriptor

Correct Answer: It often requires a homologous series of structurally related compounds

Q14. Which statistical test assesses the overall significance of a multiple regression Hansch model?

  • Student’s t-test for a single coefficient only
  • F-test for overall regression significance
  • Mann-Whitney U test
  • Fisher’s exact test for contingency tables

Correct Answer: F-test for overall regression significance

Q15. High r2 for the training set but low q2 typically indicates:

  • Excellent predictive power on external data
  • Model underfitting
  • Overfitting to the training data
  • Perfect descriptor orthogonality

Correct Answer: Overfitting to the training data

Q16. If the coefficient for σ (Hammett) is negative in a Hansch equation, which substitution trend is suggested?

  • Electron-withdrawing substituents increase activity
  • Electron-donating substituents increase activity
  • Steric bulk is the sole determinant of activity
  • Electronic effects are irrelevant

Correct Answer: Electron-donating substituents increase activity

Q17. A practical rule of thumb for dataset size in QSAR is:

  • Use at least 1 compound per descriptor
  • Use at least 5–10 compounds per descriptor to avoid overfitting
  • Always use fewer compounds than descriptors
  • Dataset size does not matter for regression models

Correct Answer: Use at least 5–10 compounds per descriptor to avoid overfitting

Q18. A positive π value for a substituent means:

  • The substituent makes the molecule more hydrophilic than hydrogen
  • The substituent increases lipophilicity relative to hydrogen
  • The substituent reduces molecular size
  • The substituent is strongly electron-withdrawing

Correct Answer: The substituent increases lipophilicity relative to hydrogen

Q19. The original formalism combining substituent constants and regression in classical QSAR is commonly called:

  • CoMFA (Comparative Molecular Field Analysis)
  • Hansch-Fujita analysis (Hansch analysis)
  • Molecular docking
  • Pharmacophore mapping

Correct Answer: Hansch-Fujita analysis (Hansch analysis)

Q20. For activity values spanning orders of magnitude, which practice is recommended before regression?

  • Use raw percent inhibition values
  • Transform IC50 values to pIC50 or log(1/IC50)
  • Discard values greater than 10 μM
  • Only use the most potent compound

Correct Answer: Transform IC50 values to pIC50 or log(1/IC50)

Q21. How should outliers in a Hansch data set be handled?

  • Always remove them without documentation
  • Investigate cause (experimental error, wrong structure), justify removal or use robust methods
  • Replace them with the mean value
  • Ignore them and proceed

Correct Answer: Investigate cause (experimental error, wrong structure), justify removal or use robust methods

Q22. Which method helps reveal nonlinearity in the relationship between descriptors and activity?

  • Residual plots and adding polynomial (e.g., squared) terms
  • Only computing molecular weight
  • Using raw IC50 without transformation
  • Performing a simple t-test

Correct Answer: Residual plots and adding polynomial (e.g., squared) terms

Q23. Which of the following is a steric descriptor commonly used in Hansch analysis?

  • Hammett σ
  • Hansch π
  • Taft Es
  • pKa

Correct Answer: Taft Es

Q24. To improve a weak Hansch model one might:

  • Add irrelevant descriptors until r2 is 1.0
  • Increase the dataset size, select meaningful descriptors, and remove collinear variables
  • Use only the most hydrophobic compounds
  • Always prefer the simplest unvalidated model

Correct Answer: Increase the dataset size, select meaningful descriptors, and remove collinear variables

Q25. How is lipophilicity (π or log P) often useful in ADME predictions within Hansch-type studies?

  • It directly gives the metabolic half-life in hours
  • It correlates with membrane permeability and distribution tendencies
  • It predicts protonation state at physiological pH with certainty
  • It replaces the need for any in vitro ADME testing

Correct Answer: It correlates with membrane permeability and distribution tendencies

Q26. A variance inflation factor (VIF) greater than which value commonly indicates problematic multicollinearity?

  • 0.1
  • 1
  • 5–10 (commonly used thresholds)
  • 1000

Correct Answer: 5–10 (commonly used thresholds)

Q27. If the coefficient of the π^2 term is negative in a Hansch equation, it suggests:

  • A linear increasing trend with lipophilicity
  • A concave parabolic relationship with an optimum lipophilicity
  • No relationship between lipophilicity and activity
  • That steric effects dominate the model

Correct Answer: A concave parabolic relationship with an optimum lipophilicity

Q28. In regression-based Hansch models, a p-value less than 0.05 for a coefficient is generally interpreted as:

  • The coefficient is statistically significant at the 5% level
  • The model is invalid
  • The descriptor has no effect
  • The model must be nonlinear

Correct Answer: The coefficient is statistically significant at the 5% level

Q29. Which practice best strengthens the predictive credibility of a Hansch QSAR model?

  • Reporting only the highest r2 from multiple trials
  • Using an external test set for validation in addition to cross-validation
  • Using the same data for training and testing without cross-validation
  • Using uncurated literature data without checks

Correct Answer: Using an external test set for validation in addition to cross-validation

Q30. How does classical Hansch analysis fundamentally differ from 3D-QSAR methods like CoMFA?

  • Hansch uses 3D electrostatic fields while CoMFA uses only 1D descriptors
  • Hansch relies on 1D/2D substituent descriptors and regression; CoMFA uses 3D steric/electrostatic fields and alignment
  • They are identical approaches with different names
  • Hansch requires protein structures while CoMFA does not

Correct Answer: Hansch relies on 1D/2D substituent descriptors and regression; CoMFA uses 3D steric/electrostatic fields and alignment

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