ProfessorGrover Miller

Member Winthrop P. Rockefeller Cancer Institute

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 goals are to assess the biological significance of metabolic activation and clearance of molecules especially related to pharmacological and toxicological effects. In practice, my group leverages powerful analytical and biochemical tools to identify and quantitate small molecules including drugs, pollutants, and food additives during metabolism and correlate findings to biological activity and in vivo outcomes such as liver toxicity. Individual projects aim to (1) determine metabolic mechanisms, efficiencies, and fluxes for activation and elimination of toxic molecules, (2) identify metabolite biomarkers in humans and animal models for correlating in vitro findings to in vivo outcomes and leveraging their diagnostic, theragnostic, and prognostic potential, and (3) develop computational models for drug bioactivation and clearance contributing to adverse drug events to make drugs safer for clinical use. Moreover, I seek translation of novel analytical and diagnostic tools into practical, commercially viable tools. Over time, my research expanded from detailed in vitro metabolic studies to metabolite profiling for translational studies and development of models of metabolism, structure, and reactivity that were made possible through strong, interdisciplinary collaborations.

  1. Computational models of metabolism provide a powerful strategy to decrease the time, effort, and costs necessary for interpreting and predicting bioactivation and elimination of drugs, pollutants, and food additives. My group began exploring models for kinetic constants and reported the first use of chirality codes and artificial neural networks to model enantioselective enzymatic reactions. Later, we teamed up with Dr. S Josh Swamidass, an expert in machine learning and modeling, to create and validate models of metabolism computationally and experimentally. The productivity of this interdisciplinary collaboration has led to sixteen published manuscripts (with another under review) and secured two multi-PI NIH R01 grants so that we can apply this novel strategy to model reactivity of drug metabolites impacting adverse drug events like drug-induced liver injury (DILI) and model changes in liver metabolism of drugs during development.
  • 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.
  • 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.
  • Dang, NL, TB, Miller, GP, Swamidass, SJ (2017) Computational Approach to Structural Alerts: Furans, Phenols, Nitroaromatics, and Thiophenes, Chem Res Toxicol 30, 1046-1059.
    Contribution to the System Toxicology II Special Issue
  • Barnette, DA, Davis, MA, Flynn, N, Pidugu, AS, Swamidass, SH, Miller, GP (2019) Comprehensive kinetic and modeling analyses revealed CYP2C9 and 3A4 determine terbinafine metabolic clearance and bioactivation, Biochem Pharmacol 170:113661. doi: 10.1016/j.bcp.2019.113661. [Epub ahead of print] (open access).

 

  1. Knowledge of metabolic mechanisms of activation and clearance of xenobiotics (e.g., drugs, pollutants, and dietary compounds) is essential for understanding and predicting in vivo consequences of on human health. As an NIH postdoctoral fellow under Dr. F. Peter Guengerich, I used a wide array of experimental and computational methods to study cytochrome P450 enzymes and reveal crucial details governing rate-limiting steps in catalysis (CYP1A2), novel interactions at multiple sites (CYP1A2 and 3A4), and protonation state of ligands (CYP2D6). After establishing my lab, I applied my multidisciplinary approach to study details explaining catalysis by CYP2B1, 2C9, 2C19, and 2E1, as well as reductive and conjugative metabolic enzymes. We are the first to show multisite binding and non-Michaelis-Menten mechanisms for CYP2E1 that could profoundly impact toxicological outcomes. We expanded efforts to understand how CYP2E1 subcellular localization impacts catalysis and toxicological mechanisms.
  • Hartman, JH, Letzig, LG, Roberts, DW, James, LP, Fifer, EK, Miller, GP (2015) Cooperativity in CYP2E1 Metabolism of Acetaminophen and Styrene Mixtures. Biochem Pharmacol 97, 341-9.
  • Hartman, JH, Martin, HC, Caro, AA, Pearce, AR, Miller, GP (2015) Subcellular Localization of Rat CYP2E1 Impacts Metabolic Efficiency toward Common Substrates. Toxicol 338, 47-58.
  • Hartman, JH, Miller, GP, Caro, AA, Byrum, SD, Orr, LM, Mackintosh, SG, Tackett, AJ, Macmillon-Crow, LA, Hallberg, LA, Ameredes, BT, Boysen, G (2016) 1,3-Butadiene-Induced Mitochondrial Dysfunction is Correlated with Mitochondrial CYP2E1 Activity in Collaborative Cross Mice, Toxicol 378, 114-124.
    Both Miller, GP and Boysen, G are corresponding authors on this manuscript

 

  1. Coumadin (R/S-warfarin) is a commonly prescribed, highly efficacious anticoagulant; however, warfarin therapy is challenging due to a narrow therapeutic range and high interindividual variation in response due to drug metabolism. Consequently, our goal is to leverage metabolite profiles to better understand the clinical relevance of warfarin metabolism and identify biomarkers for dose-responses. We were the first to develop, validate, and patent a rapid, powerful UPLC-MS method to quantitate all 14 warfarin isomeric analytes simultaneously in plasma (US Patent 8,608,967 “Multiple Stationary Phase Matrix and Uses Thereof”). We are also elucidating novel or poorly studied reductive, oxidative, and glucuronidation The ability to better understand and monitor warfarin metabolism could help interprete and predict dose-responses for managing anticoagulant therapy and improving health outcomes.
  • Jones, DR, Boysen, G, Miller, GP (2011) Novel Dual-Phase Ultra Performance Liquid Chromatography–Tandem Mass Spectrometry Assay for Profiling Enantiomeric Hydroxywarfarins and Warfarin in Human Plasma, J Chromatogr B 879, 1056-62. PMID: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.
  • Pouncey DL, Hartman JH, Moore PC, Dillinger DJ, Dickerson KW, Sappington DR, Smith ES 3rd, Boysen G,Miller GP (2018) Novel isomeric metabolite profiles correlate with warfarin metabolism phenotype during maintenance dosing in a pilot study of 29 patients, Blood Coagul Fibrinolysis 29, 602-612.

 

Complete List of Published Work in My Bibliography