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Liu J, Vernikovskaya D, Bora G, Carlo A, Burchett W, Jordan S, Tang LWT, Yang J, Che Y, Chang G, Troutman MD, Di L. Novel Multiplexed High Throughput Screening of Selective Inhibitors for Drug-Metabolizing Enzymes Using Human Hepatocytes. AAPS J 2024; 26:36. [PMID: 38546903 DOI: 10.1208/s12248-024-00908-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 03/07/2024] [Indexed: 04/02/2024] Open
Abstract
Selective chemical inhibitors are critical for reaction phenotyping to identify drug-metabolizing enzymes that are involved in the elimination of drug candidates. Although relatively selective inhibitors are available for the major cytochrome P450 enzymes (CYP), they are quite limited for the less common CYPs and non-CYPs. To address this gap, we developed a multiplexed high throughput screening (HTS) assay using 20 substrate reactions of multiple enzymes to simultaneously monitor the inhibition of enzymes in a 384-well format. Four 384-well assay plates can be run at the same time to maximize throughput. This is the first multiplexed HTS assay for drug-metabolizing enzymes reported. The HTS assay is technologically enabled with state-of-the-art robotic systems and highly sensitive modern LC-MS/MS instrumentation. Virtual screening is utilized to identify inhibitors for HTS based on known inhibitors and enzyme structures. Screening of ~4600 compounds generated many hits for many drug-metabolizing enzymes including the two time-dependent and selective aldehyde oxidase inhibitors, erlotinib and dibenzothiophene. The hit rate is much higher than that for the traditional HTS for biological targets due to the promiscuous nature of the drug-metabolizing enzymes and the biased compound selection process. Future efforts will focus on using this method to identify selective inhibitors for enzymes that do not currently have quality hits and thoroughly characterizing the newly identified selective inhibitors from our screen. We encourage colleagues from other organizations to explore their proprietary libraries using a similar approach to identify better inhibitors that can be used across the industry.
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Affiliation(s)
- Jianhua Liu
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Daria Vernikovskaya
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Gary Bora
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Anthony Carlo
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Woodrow Burchett
- Global Biometrics and Data Management, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Samantha Jordan
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Lloyd Wei Tat Tang
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Joy Yang
- Medicinal Chemistry, Pfizer Worldwide Research and Development, Cambridge, Massachusetts, USA
| | - Ye Che
- Discovery Sciences, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - George Chang
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Matthew D Troutman
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA
| | - Li Di
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, Connecticut, USA.
- Recursion Pharmaceuticals, Salt Lake City, UT, USA.
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Di L. Recent advances in measurement of metabolic clearance, metabolite profile and reaction phenotyping of low clearance compounds. Expert Opin Drug Discov 2023; 18:1209-1219. [PMID: 37526497 DOI: 10.1080/17460441.2023.2238606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 07/17/2023] [Indexed: 08/02/2023]
Abstract
INTRODUCTION Low metabolic clearance is usually a highly desirable property of drug candidates in order to reduce dose and dosing frequency. However, measurement of low clearance can be challenging in drug discovery. A number of new tools have recently been developed to address the gaps in the measurement of intrinsic clearance, identification of metabolites, and reaction phenotyping of low clearance compounds. AREAS COVERED The new methodologies of low clearance measurements are discussed, including the hepatocyte relay, HepatoPac®, HμREL®, and spheroid systems. In addition, metabolite formation rate determination and in vivo allometric scaling approaches are covered as alternative methods for low clearance measurements. With these new methods, measurement of ~ 20-fold lower limit of intrinsic clearance can be achieved. The advantages and limitations of each approach are highlighted. EXPERT OPINION Although several novel methods have been developed in recent years to address the challenges of low clearance, these assays tend to be time and labor intensive and costly. Future innovations focusing on developing systems with high enzymatic activities, ultra-sensitive universal quantifiable detectors, and artificial intelligence will further enhance our ability to explore the low clearance space.
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Affiliation(s)
- Li Di
- Research Fellow, Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, CT, USA
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Doran AC, Burchett W, Landers C, Gualtieri GM, Balesano A, Eng H, Dantonio AL, Goosen TC, Obach RS. Defining the Selectivity of Chemical Inhibitors Used for Cytochrome P450 Reaction Phenotyping: Overcoming Selectivity Limitations with a Six-Parameter Inhibition Curve-Fitting Approach. Drug Metab Dispos 2022; 50:DMD-AR-2022-000884. [PMID: 35777846 DOI: 10.1124/dmd.122.000884] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/08/2022] [Accepted: 06/09/2022] [Indexed: 11/22/2022] Open
Abstract
The utility of chemical inhibitors in cytochrome P450 (CYP) reaction phenotyping is highly dependent on their selectivity and potency for their target CYP isoforms. In the present study, seventeen inhibitors of CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, and 3A4/5 commonly used in reaction phenotyping were evaluated for their cross-enzyme selectivity in pooled human liver microsomes. The data were evaluated using a statistical desirability analysis to identify (1) inhibitors of superior selectivity for reaction phenotyping and (2) optimal concentrations for each. Among the inhibitors evaluated, α-naphthoflavone, furafylline, sulfaphenazole, tienilic acid, N-benzylnirvanol, and quinidine were most selective, such that their respective target enzymes were inhibited by ~95% without inhibiting any other CYP enzyme by more than 10%. Other commonly employed inhibitors, such as ketoconazole and montelukast, among others, were of insufficient selectivity to yield a concentration that could adequately inhibit their target enzymes without affecting other CYP enzymes. To overcome these shortcomings, an experimental design was developed wherein dose response data from a densely sampled multi-concentration inhibition curve are analyzed by a six-parameter inhibition curve function, allowing accounting of the inhibition of off-target CYP isoforms inhibition and more reliable determination of maximum targeted enzyme inhibition. The approach was exemplified using rosiglitazone N-demethylation, catalyzed by both CYP2C8 and 3A4, and was able to discern the off-target inhibition by ketoconazole and montelukast from the inhibition of the targeted enzyme. This methodology yields more accurate estimates of CYP contributions in reaction phenotyping. Significance Statement Isoform-selective chemical inhibitors are important tools for identifying and quantifying enzyme contributions as part of a CYP reaction phenotyping assessment for projecting drug-drug interactions. However, currently employed practices fail to adequately compensate for shortcomings in inhibitor selectivity and the resulting confounding impact on estimates of the CYP enzyme contribution to drug clearance. In this report, we describe a detailed IC50 study design with 6-parameter modeling approach that yields more accurate estimates of enzyme contribution.
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Affiliation(s)
| | | | | | | | | | - Heather Eng
- Pharmacokinetics, Dynamics, and Metabolism, Pfizer Global Research and Development, United States
| | | | - Theunis C Goosen
- Pharmacokinetics, Dynamics & Metabolism, Pfizer, Inc, United States
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