Professor

NIH postdoctoral fellow, Vanderbilt University, 1999-2001
Ph.D., Pennsylvania State University, 1997
B.S., Louisiana State University, 1992

E-mailMillerGroverP@uams.edu
Office:  (501)526-6486 – Biomedical Research Center B421A
Lab:  (501)526-6487 – Biomedical Research Center B420
FAX:  (501)686-8169

Research Specialty:

My research group investigates the role of enzymes, especially cytochromes P450 (CYP), in the activation and processing of xenobiotic chemicals, such as drugs, pollutants, and dietary compounds, from a chemist’s perspective. We specialize in the identification and validation of biochemical mechanisms through experimental approaches and often develop analytical tools along the way. Nevertheless, our projects are often multi-disciplinary and collaborative to effectively tackle complex challenges by recruiting experts in computational, analytical, and clinical research.

  1. Molecular mechanisms of detoxification and bioactivation of xenobiotic compounds

Xenobiotic molecules comprise a structurally and functionally diverse array of “foreign” molecules that possess biological activities, such as drugs, pollutants, and dietary compounds, and hence their metabolic clearance requires enzymes possessing broad specificities to accommodate this molecular diversity. Those qualities create a significant challenge to characterizing specificities and efficiencies of metabolism and assessing their role in the clearance and/or bioactivation of xenobiotic compounds. Consequently, my group employs a wide array of experimental methods to study binding and catalysis using computational software to integrate information and identify the most probable mechanism among multiple possiblities. Those efforts have revealed crucial details governing rate-limiting steps in catalysis (CYP1A2), novel interactions at multiple sites (CYP1A2 and 3A4), and the protonation state of ligands (CYP2D6). More recently, we applied this multi-disciplinary approach to study details explaining catalysis by CYP2B1, 2C9, 2C19, and especially 2E1. My group was the first to propose and validate a mechanism for CYP2E1 substrate inhibition toward 4-nitrophenol after over 20 years of its use as a marker substrate. Subsequent binding, inhibition, and catalytic studies revealed novel cooperative mechanisms for CYP2E1 toward aniline, azoles, and styrene as we expand our focus to important drugs and pollutants metabolized by CYP2E1. Based on those models, non-Michaelis-Menten mechanisms for CYP2E1 could have profound impacts on toxicological outcomes, especially those involving mixtures, and may explain observed discrepancies in findings among in vivo data from exposure studies. Consequently, the assessment of the toxicological relevance of these biochemical mechanisms is a new area of focus for our research.

Collom, SL, Laddusaw, RM, Kuzmic, P, Burch, AM, Perry, Jr, MD, Miller, GP (2008) CYP2E1 Substrate Inhibition: Mechanistic interpretation through an effector site for monocyclic compounds. J Biol Chem 283, 3487-96. PMC3933162 [http://www.ncbi.nlm.nih.gov/pubmed/18056994]

Hartman, JH, Gunnar Boysen, G, Miller, GP, (2012) CYP2E1 Metabolism of Styrene Involves Allostery, Drug Metab Dispos 40, 1976-83. PMC3463823 [http://www.ncbi.nlm.nih.gov/pubmed/22807108]

Hartman, JH, Knott, AK, Miller GP (2014) CYP2E1 Hydroxylation of Aniline Involves Negative Cooperativity, Biochem Pharmacol 87, 523-33. PMID24345333 [http://www.ncbi.nlm.nih.gov/pubmed/24345333]

Hartman, JH, Letzig, LG, Roberts, DW, James, LP, Fifer, EK, Miller, GP (2015) Cooperativity in CYP2E1 Metabolism of Acetaminophen and Styrene Mixtures, Biochem Pharmacol, in press. [http://www.ncbi.nlm.nih.gov/pubmed/26225832]

  1. Clinical relevance of warfarin metabolism as revealed through metabolite profiling

Coumadin (R/S-warfarin) is a commonly prescribed, highly efficacious anticoagulant; however, warfarin therapy is challenging due to a narrow therapeutic range and high inter-individual variation in response due to drug metabolism. The relative significance of metabolic pathways will depend on factors like lifestyle choices, genetics, and drug interactions (induction and inhibition) that influence metabolism and alter metabolite levels as reflected in the warfarin metabolic phenotype for a patient. In collaboration with Gunnar Boysen (Metabolomics Core, UAMS), my team was the first to develop and validate a rapid, powerful UPLC-MS method that directly quantitates all 14 warfarin isomeric analytes simultaneously from a single plasma sample. We are leveraging this tool to understand causes for variations in patient dose-responses related to metabolism and identify biomarkers for predicting those outcomes in translational clinical studies funded by AHA and NIH-supported Translational Research Institute (UAMS). At the same time, we use biochemical tools to elucidate novel or poorly characterized oxidative pathways, e.g. those involving CYP2C19 and (pediatric) CYP3A7, and glucuronidation pathways relying on collaboration with Tom Goodwin (Hendrix College) to synthesize authentic standards. The ability to better understand and monitor warfarin metabolism could facilitate the interpretation and prediction of dose-responses as a new tool for managing anticoagulant therapy and improving health outcomes.

Jones, DR, Kim, SY, Guderyon, M, Yun, CH, Moran, J, Miller, GP (2010) Hydroxywarfarin Metabolites Potently Inhibit CYP2C9 Metabolism of S-Warfarin, Chem Res Tox 23, 939-45. PMID20429590 [http://www.ncbi.nlm.nih.gov/pubmed/20429590]

Jones, DR, Kim, SY, Boysen, G, Yun, CH, Miller, GP (2010) Contribution of Three CYP3A Isoforms to Metabolism of R- and S-Warfarin, Drug Metab Lett 4, 213-9. PMID20615193 [http://www.ncbi.nlm.nih.gov/pubmed/20615193]

Jones, DR, Boysen, G, Miller, GP (2011) Novel Multi-Mode Ultra Performance Liquid Chromatography–Tandem Mass Spectrometry Assay for Profiling Enantiomeric Hydroxywarfarins and Warfarin in Human Plasma, J Chromatogr B 879, 1056-62. PMID21470921 [http://www.ncbi.nlm.nih.gov/pubmed/21470921]

Pugh, CP, Pouncey, DL, Hartman, JH, Nshimiyimana, R, Desrochers, LP, Goodwin, TE, Boysen, G, Miller, GP (2014) Multiple UDP- Glucuronosyltransferases in Human Liver Microsomes Glucuronidate Both R- and S-7-Hydroxywarfarin into Two Metabolites, Arch Biochem BIophys 564, 244-53. PMID25447818 [http://www.ncbi.nlm.nih.gov/pubmed/25447818]

  1. Computational models of metabolism and reactivity

Computational models of P450 metabolism provide a powerful strategy to decrease the time, effort, and costs required for obtaining knowledge for interpreting and predicting bioactivation and elimination of drugs, pollutants, and food additives. Through collaboration with Dr. Martin D Perry Jr (Ouachita Baptist University), my group explored protein-ligand docking to identify and assess possible CYP2E1 catalytic and effector sites that modulate catalytic efficiency through non-Michaelis-Menten mechanisms. Recently, we coupled docking efforts to Molecular Dynamics simulations and modeled CYP2E1 conformational flexibility during binding for a series of azoles. Those studies provided critical insights on structure-function relationships governing azole substituent effects on stoichiometry and affinity for CYP2E1 based on binding and catalytic inhibition studies. I initiated another computational project to predict which reactions occur and how efficiently they proceed as reflected in their metabolic constants. My group reported the first use of chirality codes and artificial neural networks to model enantioselective reactions for CYP2C19. As a follow up, we have teamed up with Dr. S Josh Swamidass (University of Washington-St Louis), an expert in machine learning and modeling, to combine our strengths for creating and validating models of metabolism and reactivity of drugs, pollutants, and dietary compounds.

Hartman, JH, Cothren, SD, Park, SH, Yun, CH, Darsey, JA, Miller, GP (2013) Predicting CYP2C19 Catalytic Parameters for Enantioselective Oxidations Using Artificial Neural Networks and a Chirality Code, Bioorg Med Chem 21, 3749-59. PMC3674096 [http://www.ncbi.nlm.nih.gov/pubmed/23673224]

Levy, JW, Hartman, JH, Perry Jr, MD, Miller, GP (2015) Structural Basis for Cooperative Binding of Azoles to CYP2E1 as Interpreted through Guided Molecular Dynamics Simulations, J Mol Graph Model 56C, 43-52. PMID25544389 [http://www.ncbi.nlm.nih.gov/pubmed/25544389]

Hughes, TB, Miller, GP, Swamidass, SJ (2015) Site of Reactivity Models Predict Molecular Reactivity of Diverse Chemicals with Glutathione, Chem Res Tox, in press. [http://www.ncbi.nlm.nih.gov/pubmed/25742281]

Hughes, TB, Miller, GP, Swamidass, SJ (2015) Modeling Epoxidation of Drug-Like Molecules with a Deep Machine Learning Network, ACS Central Sci, in press. [http://pubs.acs.org/doi/abs/10.1021/acscentsci.5b00131]

Complete List of Published Work in My Bibliography