Biology subjects

Wen, Y. W.

Publications and source records attributed to Wen, Y. W..

4 recordsLinked to original sources

bioRxiv2026

Liver Fatty Acid Binding Protein (FABP1) Affects Cytochrome P450 2C9 (CYP2C9)-Mediated Metabolism in Human Liver Models

Metabolic clearance of drugs is often systematically over- or underpredicted from human liver microsomes (HLM). We hypothesized that lack of consideration of interactions of cytosolic liver fatty acid binding protein (FABP1) with drugs and cytochrome P450s (CYPs) explains the off-prediction. We used two CYP2C9 probe substrates, diclofenac and tolbutamide, to test this hypothesis. We found that presence of FABP1 alters the kinetics of metabolite formation in HLM. The model that best fit the kinetic data included FABP1-CYP2C9 protein-protein interactions. Statistical modeling of proteomic expression and drug hydroxylation across a panel of 61 human liver S9 fractions (HLS9) showed that CYP2C9 and FABP1 expression together best predicted probe substrate hydroxylation. Incorporation of FABP1 expression and protein-protein interactions into novel physiologically based liver models significantly improved the quantitative accuracy of in vivo hepatic clearance prediction. Together, our data demonstrate the importance of taking FABP1 into consideration for CYP2C9-mediated metabolism.

pharmacology and toxicology↗

bioRxiv2026

Characterization of Cytochrome P450-Mediated Metabolism of Δ8-tetrahydrocannabinol in vitro

{Delta}-tetrahydrocannabinol ({Delta}8-THC) is a pharmacologically active isomer of {Delta}9-THC, the main psychoactive component of cannabis. {Delta}8-THC use has increased rapidly, but the metabolism of {Delta}8-THC has been incompletely characterized. This study identified metabolites of {Delta}8-THC formed by cytochrome P450 (CYP) enzymes in human liver microsomes (HLM), assigned the main CYPs responsible for the metabolic pathways, and evaluated the impact of genetic polymorphisms on {Delta}8-THC metabolism in vitro. Five monohydroxylated {Delta}8-THC metabolites, identified as 11-OH-{Delta}8-THC, two aliphatic side-chain hydroxylated products (M1, M2), and two ring hydroxylated products (M3, M4) were detected in HLM. 11-OH-{Delta}8-THC was the most abundant metabolite. Unbound binding constants for metabolite formation in HLM ranged from 3.6 nM to >121 nM, suggesting multiple enzymes contribute to {Delta}8-THC metabolism. The contributing enzymes were identified using recombinant CYPs, inhibition studies, and correlation analyses. 11-OH-{Delta}8-THC was predominantly formed by CYP2C9 with a minor contribution from CYP2C19. CYP2C9 genotype-based activity scores across donors correlated with 11-OH-{Delta}8-THC formation (p = 0.0315). An 80% decrease in 11-OH-{Delta}8-THC formation clearance was predicted in CYP2C9*3/*3 carriers. The ring-hydroxylated M3 and M4 were mainly formed by CYP3A. CYP2D6, CYP1A2, and CYP3A4 activities were associated with formation of the pentyl side-chain oxidized metabolites M1 and M2. Although C11 hydroxylation appeared more important metabolic pathway for {Delta}8-THC than for {Delta}9-THC, the catalytic efficiency of CYP2C9 towards {Delta}8-THC was lower than towards {Delta}9-THC. In the presence of CYP2C9 inhibitors or genetic polymorphisms, {Delta}8-THC clearance is likely mediated by CYP3A4 and CYP2C19. This study shows that 11-OH-{Delta}8-THC, a psychoactive metabolite, is the primary oxidation product of {Delta}8-THC in HLM and that CYP2C9 predominantly catalyzes its formation. This work expands the limited literature on {Delta}8-THC metabolism, and shows that reduced-function CYP2C9 variants substantially impair formation of 11-OH-{Delta}8-THC. The characterization of {Delta}8-THC metabolism in HLM provides the foundation for risk assessment of drug-drug interactions and establishes the metabolic profile of {Delta}8-THC in the human liver.

pharmacology and toxicology↗

bioRxiv2026

Development of Physiologically Based Liver Distribution Model that Incorporates Intracellular Lipid Partitioning and Binding to Fatty Acid Binding Protein 1 (FABP1)

Steady-state volume of distribution (Vss) can be predicted using tissue-to-plasma partition coefficients (Kp) and tissue volumes. Kp values are important components of physiologically based pharmacokinetic (PBPK) models, allowing for estimation of distribution kinetics and simulation of concentration-time profiles. Many in silico approaches have been developed to predict tissue Kp values based on physicochemical processes that govern drug distribution. However, these methods frequently over- or under-predict tissue Kp values, highlighting the need to consider additional mechanisms that can impact drug distribution kinetics. Many drugs have been shown to bind to rat and human fatty acid binding proteins (FABPs) in vitro but the impact of this binding to drug distribution has not been incorporated into Kp predictions. We hypothesized that incorporating intracellular protein binding into tissue Kp predictions will improve Kp prediction accuracy. Using liver as a model organ, four physiologically based dynamic liver distribution models (LDMs) were developed to assess the role of distribution processes in Kp predictions. The developed LDMs incorporated known distribution mechanisms and intracellular drug binding to liver FABP (FABP1). The liver Kp values for drugs that bind to FABP1 were accurately predicted using the LDM that incorporates lipid partitioning, albumin distribution, and FABP1 binding but not using LDMs without FABP1 binding. Human FABP1 expression was quantified in 61 human livers and the interindividual variability in tissue FABP1 binding was incorporated into tissue Kp predictions. These simulations showed that intracellular FABP1 binding can cause interindividual variability in Kp values and result in concentration dependent tissue distribution. Significance StatementThis study shows that incorporating intracellular protein binding such as binding to FABP1 into tissue Kp predictions improves accuracy of the predictions. The novel dynamic LDM can be extrapolated to other organs of interest and integrated into full-body PBPK models to predict drug distribution kinetics. With dynamic and saturable distribution mechanisms incorporated into a PBPK model, nonlinear distribution kinetics can be simulated for various drugs.

pharmacology and toxicology↗

bioRxiv2026

Proteomic Profiling of Human Omental and Subcutaneous Adipose Tissue in Individuals with a Broad Range of BMI.

Obesity is a major public health challenge affecting an ever-increasing proportion of the global population. It is associated with numerous comorbidities. Progressive expansion and remodeling of adipose tissue may lead to depot specific changes in adipose tissue biology and energy partitioning. Such changes likely precede the development of obesity-related complications. To facilitate a deeper understanding of adipose tissue biology, a comprehensive and quantitative proteomic dataset at the peptide and protein level is presented. Data-independent acquisition LC-MS/MS data were acquired from matched subcutaneous and omental adipose tissues from metabolically healthy individuals with no comorbidities and covering a wide range of body mass indexes. Adipose tissue samples were collected during elective surgeries and immediately processed for histology or frozen until proteomic analysis. Internal and external quality control systems ensured high quality data. All data presented are available via ProteomeXchange. This dataset will allow new insights into biological changes that evolve with increasing adiposity captured before the onset of comorbidities. Matched sampling across fat depots provides an opportunity to uncover depot-specific physiological signatures.

systems biology↗