Interaction of Three Regiospecific Amino Acid Residues Is Required for OATP1B1 Gain of OATP1B3 Substrate Specificity

The human organic anion-transporting polypeptides OATP1B1 (<i>SLCO1B1</i>) and OATP1B3 (<i>SLCO1B3</i>) are liver-enriched membrane transporters of major importance to hepatic uptake of numerous endogenous compounds, including bile acids, steroid conjugates, hormones, and drugs, including the 3-hydroxy-3-methylglutaryl Co-A reductase inhibitor (statin) family of cholesterol-lowering compounds. Despite their remarkable substrate overlap, there are notable exceptions: in particular, the gastrointestinal peptide hormone cholecystokinin-8 (CCK-8) is a high affinity substrate for OATP1B3 but not OATP1B1. We utilized homologous recombination of linear DNA by <i>E. coli</i> to generate a library of cDNA containing monomer size chimeric OATP1B1–1B3 and OATP1B3–1B1 transporters with randomly distributed chimeric junctions to identify three discrete regions of the transporter involved in conferring CCK-8 transport activity. Site-directed mutagenesis of three key residues in OATP1B1 transmembrane helices 1 and 10, and extracellular loop 6, to the corresponding residues in OATP1B3, resulted in a gain of CCK-8 transport by OATP1B1. The residues appear specific to CCK-8, as the mutations did not affect transport of the shared OATP1B substrate atorvastatin or the OATP1B1-specific substrate estrone sulfate. Regions involved in gain of CCK-8 transport by OATP1B1, when mapped to the crystal structures of bacterial transporters from the major facilitator superfamily, are positioned to suggest these regions could readily interact with drug substrates. Accordingly, our data provide new insight into the molecular determinants of the substrate specificity of these hepatic uptake transporters with relevance to targeted drug design and prediction of drug–drug interactions

Model predicted response curves following warfarin initiation using various initiation protocols.

<p>Simulations were performed using non-genetics and genetics-based nomograms for typical AF and VTE patients harbouring variable number of variant alleles. The genotype of zero-variant patients is <i>VKORC1</i>G/G-<i>CYP2C9</i>^*1/^*1. Patients carrying 1 variant allele have one of the following genotype combinations: <i>VKORC1</i>G/A-<i>CYP2C9</i>^*1/^*1, <i>VKORC1</i>G/G-<i>CYP2C9</i>^*1/^*2, or <i>VKORC1</i>G/G-<i>CYP2C9</i>^*1/^*3. Patients carrying 2 variant alleles have one of the following genotype combinations: <i>VKORC1</i>A/A-<i>CYP2C9</i>^*1/^*1, <i>VKORC1</i>G/A-<i>CYP2C9</i>^*1/^*2, <i>VKORC1</i>G/A-<i>CYP2C9</i>^*1/^*3, or <i>VKORC1</i>G/G-<i>CYP2C9</i>^*2/^*2. Patients carrying 3 variant alleles have one of the following genotype combinations: <i>VKORC1</i>A/A-<i>CYP2C9</i>^*1/^*2, <i>VKORC1</i>A/A-<i>CYP2C9</i>^*1/^*3, <i>VKORC1</i>G/A-<i>CYP2C9</i>^*2/^*2, or <i>VKORC1</i>G/A-<i>CYP2C9</i>^*2/^*3. Patients carrying 4 variant alleles have one of the following genotype combinations: <i>VKORC1</i>A/A-<i>CYP2C9</i>^*2/^*2, or <i>VKORC1</i>A/A-<i>CYP2C9</i>^*2/^*3. AF, atrial fibrillation; VTE, venous thromboembolism.</p

Multiple linear regression analysis of independent predictors of <i>S</i>-warfarin clearance (L/day).

<p>CI, confidence interval; <i>CYP2C9</i>, cytochrome P450 2C9; eGFR, estimated glomerular filtration rate in mL/min/1.73m²; F, female.</p>a<p>Coded as follows: ≥90 mL/min/1.73 m², 0; 60–89, 1; 30–59, 2; 15–29, 3; ≤15, 4.</p

Determinants of <i>S</i>-warfarin clearance.

<p>(A) Frequency distribution of estimated <i>S</i>-warfarin clearance, shown as percent of total patients for each bin. (B) Relationship between <i>CYP2C9</i> genotype and <i>S</i>-warfarin clearance. Lines represent mean clearance. (C) <i>S</i>-warfarin clearance is significantly correlated with kidney function, as defined by eGFR. (D) Observed <i>S</i>-warfarin clearance segregated by gender. Lines represent mean clearance. eGFR, estimated glomerular filtration rate. ^* P<0.05, ^** P<0.005, ^***P<0.0005</p

Determinants of maximal inhibitory factor, I_max.

<p>(A) Box-and-whisker plots of <i>S</i>-warfarin plasma concentration and INR on days 7/8/9 segregated by <i>VKORC1</i> -1639G>A genotype. Box-and-whisker plots representing <i>VKORC1</i> gene-dose effect during initiation. The top and bottom of the boxes represents 25^th and 75^th percentile, respectively; median is represented by the middle line, whiskers are the 95% CI, and outliers are identified as closed circles. (B) Warfarin daily dose on days 7/8/9 with respect to <i>VKORC1</i> genotype. (C) Frequency distribution of estimated I_max, shown as percent of total patients for each bin. (D) Association between <i>VKORC1</i> genotype and I_max. Results are represented as mean with standard deviation. (E) Additive effect of indication for warfarin therapy and <i>VKORC1</i> genotype on I_max. (F) INR time course for patients with AF and VTE over the initial 10 days of therapy with common genetics-guided dosing protocol. Results are represented as mean with 95% CI of the standard error. AF, atrial fibrillation; INR, international normalized ratio; VTE, venous thromboembolism. ^* P<0.05, ^** P<0.01, ^*** P<0.001, ^**** P<0.0001.</p

The influence of <i>VKORC1</i> -1639G>A promoter genotype on hepatic VKOR protein expression levels.

<p>(A, B, C) VKOR expression determined in 17 healthy human livers by Western blot analysis. The band intensity was normalized to HLM100. A positive control sample was included on each blot. (D) Semiquantitative measurement of hepatic expression in relation to <i>VKORC1</i> genotype. ^* P<0.01</p

PK-PD model performance.

<p>(A) Model simulated <i>S</i>-warfarin plasma concentration-time profiles after single dose with <i>CYP2C9</i> variant alleles. (B) Model simulated steady-state therapeutic INR (2.5) <i>vs. S</i>-warfarin plasma concentration with varying I_max corresponding to <i>VKORC1</i> -1639G>A genotype. (C) Model fit of measured <i>S</i>-warfarin concentrations in a single patient. (D) Scatter plot of actual <i>vs.</i> predicted <i>S</i>-warfarin plasma concentration throughout the initiation phase (coefficient of determination, r² = 0.91, n = 459). The diagonal line represents the unity line. (E) Model fit of measured anticoagulation INR response values in the same patient as in (C). (F) Scatter plot of actual <i>vs.</i> predicted INR during the initiation phase (r² = 0.89, n = 459). The diagonal line represents the unity line. I_max, maximal inhibitory factor; INR, international normalized ratio.</p

Multiple linear regression analysis of independent predictors of I_max.

<p>CI, confidence interval; <i>CYP4F2</i>, cytochrome P450 4F2; I_max, maximal inhibitory factor; PIVKA-II, proteins induced by vitamin K absence; <i>VKORC1</i>, vitamin K epoxide reductase complex subunit 1; VTE, venous thromboembolism.</p