Transporter modeling (P-gp, OATP, etc.) MCQs With Answer

Introduction:

Transporter modeling is a critical component of Computer Aided Drug Development, especially for M.Pharm students learning how membrane transporters like P-glycoprotein (P-gp) and organic anion-transporting polypeptides (OATPs) influence drug disposition, efficacy, and safety. This blog presents focused multiple-choice questions that cover mechanistic concepts, experimental assays, in silico modeling approaches (QSAR, docking, molecular dynamics), kinetics and inhibition parameters, PBPK integration, and data science considerations relevant to transporter research. The questions are designed to deepen understanding of transporter-mediated ADME, help interpret experimental results, and guide rational design of substrates and inhibitors using computational tools.

Q1. Which computational approach specifically aims to predict transporter substrate affinity using 3D structural information of the transporter binding site?

• Quantitative Structure–Activity Relationship (QSAR)
• Molecular docking into homology or cryo-EM derived models
• Physiologically Based Pharmacokinetic (PBPK) modeling
• Topological polar surface area (TPSA) descriptor analysis

Correct Answer: Molecular docking into homology or cryo-EM derived models

Q2. In P-gp efflux assays using MDCK-MDR1 cells, which metric best indicates active efflux of a compound?

• Low aqueous solubility
• Efflux ratio (ER) >> 1 measured as basolateral-to-apical / apical-to-basolateral permeability
• High passive permeation across PAMPA membrane
• Large volume of distribution in vivo

Correct Answer: Efflux ratio (ER) >> 1 measured as basolateral-to-apical / apical-to-basolateral permeability

Q3. When building a ligand-based QSAR model for OATP substrates, which descriptor class is most commonly useful for capturing interactions with transporter binding pockets?

• Global PK parameters like clearance and half-life
• Physicochemical descriptors, e.g., lipophilicity (logP), molecular weight, polar surface area
• Clinical trial endpoints
• Manufacturing process impurities

Correct Answer: Physicochemical descriptors, e.g., lipophilicity (logP), molecular weight, polar surface area

Q4. In transporter inhibition studies, which parameter represents the inhibitor concentration producing 50% inhibition of transporter-mediated substrate transport and is often used as a potency metric?

• Km
• Vmax
• IC50
• EC90

Correct Answer: IC50

Q5. Which statement about homology modeling of human transporters (e.g., P-gp) is most accurate?

• Homology models are always superior to experimental cryo-EM structures for docking.
• High-quality homology models require a closely related template and careful loop refinement for accurate binding site geometry.
• Homology models do not require sequence alignment with the template.
• Transporter homology models eliminate the need for experimental validation of docking predictions.

Correct Answer: High-quality homology models require a closely related template and careful loop refinement for accurate binding site geometry.

Q6. Which kinetic parameter describes the substrate concentration at which the transporter-mediated rate is half of Vmax?

• IC50
• Km
• Ki
• Clint

Correct Answer: Km

Q7. For PBPK models incorporating transporter-mediated hepatic uptake (e.g., OATP1B1), which experimental input is most critical?

• Renal clearance in mice only
• Intrinsic uptake clearance (CLint,uptake) determined in hepatocytes or transporter-expressing cells
• Melting point of the compound
• Logistical manufacturing timelines

Correct Answer: Intrinsic uptake clearance (CLint,uptake) determined in hepatocytes or transporter-expressing cells

Q8. Which machine learning validation approach best estimates predictive performance and helps prevent overfitting for transporter QSAR models when dataset size is moderate?

• Use training set R2 only
• Leave-one-out or k-fold cross-validation with external test set validation
• Optimizing hyperparameters on the test set
• Randomly reporting the best-performing split

Correct Answer: Leave-one-out or k-fold cross-validation with external test set validation

Q9. Which molecular dynamics (MD) application is most useful after docking a substrate into a transporter model?

• Predicting compound synthesis route
• Assessing stability of ligand binding pose and protein conformational changes over time
• Measuring in vitro intrinsic clearance
• Calculating clinical trial sample size

Correct Answer: Assessing stability of ligand binding pose and protein conformational changes over time

Q10. Inhibition constant Ki is related to IC50 by a formula. For a competitive inhibitor with substrate concentration equal to Km, what is the relationship between IC50 and Ki?

• IC50 = Ki
• IC50 = 2 × Ki when [S] = Km for competitive inhibition (IC50 = Ki × (1 + [S]/Km))
• IC50 is independent of substrate concentration
• IC50 = Ki / 2

Correct Answer: IC50 = 2 × Ki when [S] = Km for competitive inhibition (IC50 = Ki × (1 + [S]/Km))

Q11. Which experimental system is most appropriate for distinguishing between P-gp mediated efflux and passive permeability limitation?

• Human liver biopsy
• Bidirectional transwell assay using MDCK-MDR1 or Caco-2 cells comparing apical-to-basolateral and basolateral-to-apical permeabilities
• Single-concentration cytotoxicity assay in hepatocytes
• In vitro dissolution testing

Correct Answer: Bidirectional transwell assay using MDCK-MDR1 or Caco-2 cells comparing apical-to-basolateral and basolateral-to-apical permeabilities

Q12. Which feature selection strategy is recommended to reduce multicollinearity and improve interpretability in transporter QSAR models?

• Keep all correlated descriptors to maximize variance
• Use variance inflation factor (VIF) filtering and recursive feature elimination
• Select descriptors randomly
• Only use molecular weight as the descriptor

Correct Answer: Use variance inflation factor (VIF) filtering and recursive feature elimination

Q13. Which statement best describes the role of conformational flexibility of P-gp in substrate recognition?

• P-gp has a rigid binding site that binds only one chemical scaffold.
• P-gp undergoes large conformational changes (inward- and outward-facing states) allowing polyspecific recognition and translocation of diverse substrates.
• P-gp functions solely as an ion channel rather than an ATP-driven transporter.
• P-gp recognizes substrates based only on molecular weight.

Correct Answer: P-gp undergoes large conformational changes (inward- and outward-facing states) allowing polyspecific recognition and translocation of diverse substrates.

Q14. In transporter modeling, what is the main advantage of using cryo-EM derived structures over homology models?

• Cryo-EM always provides exact binding energetics without simulation
• Cryo-EM can provide experimentally determined conformations and detailed binding site geometries, reducing uncertainty in docking
• Cryo-EM eliminates the need for kinetic experiments
• Cryo-EM structures are always from human proteins expressed in vivo

Correct Answer: Cryo-EM can provide experimentally determined conformations and detailed binding site geometries, reducing uncertainty in docking

Q15. When modeling transporter-mediated drug–drug interactions (DDIs), which parameter best quantifies the potential of an inhibitor to cause clinical DDI via hepatic uptake transporter inhibition?

• Maximum tolerated dose in animals
• Ratio of unbound hepatic inlet concentration to IC50 (or Ki) and mechanistic inhibitor potency integrated into PBPK simulations
• Number of hydrogen bond donors only
• Manufacturing batch size

Correct Answer: Ratio of unbound hepatic inlet concentration to IC50 (or Ki) and mechanistic inhibitor potency integrated into PBPK simulations

Q16. Which assessment metric is most appropriate for evaluating classification performance of a binary QSAR model that predicts transporter substrates versus non-substrates?

• Root mean square error (RMSE) only
• Area under the ROC curve (AUC-ROC) along with sensitivity and specificity
• pH of the formulation
• Number of stereocenters alone

Correct Answer: Area under the ROC curve (AUC-ROC) along with sensitivity and specificity

Q17. Genetic polymorphisms in transporters such as OATP1B1 can impact drug disposition. Which modeling strategy helps predict population variability due to such polymorphisms?

• Deterministic single-compartment models only
• Population PBPK modeling incorporating genotype-specific transporter expression and activity
• Ignoring genotype effects and using mean values only
• Using only in vitro microsomal clearance

Correct Answer: Population PBPK modeling incorporating genotype-specific transporter expression and activity

Q18. Which in silico descriptor is often inversely correlated with recognition by OATP transporters and can be used to prioritize compounds for uptake?

• High molecular polarity or negative charge at physiological pH (often favored by OATPs)
• Extremely high lipophilicity always favors OATP uptake
• Large aromatic surface area only
• Number of rotatable bonds without considering charge

Correct Answer: High molecular polarity or negative charge at physiological pH (often favored by OATPs)

Q19. When modeling P-gp inhibitors using structure-based methods, which factor is essential to consider to improve docking accuracy?

• Protonation state of ligand and ionizable residues in the binding site
• Total synthesis cost
• Only the ligand molecular weight
• Color of the compound powder

Correct Answer: Protonation state of ligand and ionizable residues in the binding site

Q20. For large-scale transporter substrate prediction using machine learning, which practical data curation step is most critical before model training?

• Keeping duplicated or contradictory activity records without reconciliation
• Standardizing chemical structures, removing duplicates/conflicts, normalizing activity units, and accounting for assay conditions
• Excluding descriptors to simplify the dataset arbitrarily
• Converting all molecular structures to images only

Correct Answer: Standardizing chemical structures, removing duplicates/conflicts, normalizing activity units, and accounting for assay conditions

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