PURPOSE: Typically, the kinetics of membrane transport is analyzed using the steady-state Michaelis-Menten (or Eadie-Hofstee or Hanes) equations. This approach has been successful when the substrate is picked up from the aqueous phase, like a water-soluble enzyme, for which the Michaelis-Menten steady-state analysis was developed. For membrane transporters whose substrate resides in the lipid bilayer of the plasma membrane, like P-glycoprotein (P-gp), there has been no validation of the accuracy of the steady-state analysis because the elementary rate constants for transport were not known. METHODS: Recently, we fitted the mass action elementary kinetic rate constants of P-gp transport of three different drugs through a confluent monolayer of MDCKII-hMDR1 cells. With these elementary rate constants in hand, we use computer simulations to assess the accuracy of the steady-state Michaelis-Menten parameters. This limits the simulation to parameter ranges known to be physiologically relevant. RESULTS: Using over 2,300 different vectors of initial elementary parameters spanning the space bounded by the three drugs, which defines 2,300 "virtual substrates", the concentrations of substrate transported were calculated and fitted to Eadie-Hofstee plots. Acceptable plots were obtained for 1,338 cases. CONCLUSION: The fitted steady-state Vmax values from the analysis correlated to within a factor of 2-3 with the values predicted from the elementary parameters. However, the fitted Km value could be generated by a wide range of underlying "molecular" Km values. This is because of the convolution of the drug passive permeability kinetics into the fitted Km. This implies that Km values measured in simpler systems, e.g., microsomes or proteoliposomes, even if accurate, would not predict the Km values for the confluent monolayer system or, by logical extension, in vivo. Reliable in vitro-in vivo extrapolation seems to require using the elementary rate constants rather than the Michaelis-Menten steady-state parameters.
PURPOSE: Typically, the kinetics of membrane transport is analyzed using the steady-state Michaelis-Menten (or Eadie-Hofstee or Hanes) equations. This approach has been successful when the substrate is picked up from the aqueous phase, like a water-soluble enzyme, for which the Michaelis-Menten steady-state analysis was developed. For membrane transporters whose substrate resides in the lipid bilayer of the plasma membrane, like P-glycoprotein (P-gp), there has been no validation of the accuracy of the steady-state analysis because the elementary rate constants for transport were not known. METHODS: Recently, we fitted the mass action elementary kinetic rate constants of P-gp transport of three different drugs through a confluent monolayer of MDCKII-hMDR1 cells. With these elementary rate constants in hand, we use computer simulations to assess the accuracy of the steady-state Michaelis-Menten parameters. This limits the simulation to parameter ranges known to be physiologically relevant. RESULTS: Using over 2,300 different vectors of initial elementary parameters spanning the space bounded by the three drugs, which defines 2,300 "virtual substrates", the concentrations of substrate transported were calculated and fitted to Eadie-Hofstee plots. Acceptable plots were obtained for 1,338 cases. CONCLUSION: The fitted steady-state Vmax values from the analysis correlated to within a factor of 2-3 with the values predicted from the elementary parameters. However, the fitted Km value could be generated by a wide range of underlying "molecular" Km values. This is because of the convolution of the drug passive permeability kinetics into the fitted Km. This implies that Km values measured in simpler systems, e.g., microsomes or proteoliposomes, even if accurate, would not predict the Km values for the confluent monolayer system or, by logical extension, in vivo. Reliable in vitro-in vivo extrapolation seems to require using the elementary rate constants rather than the Michaelis-Menten steady-state parameters.
Authors: K S Lown; R R Mayo; A B Leichtman; H L Hsiao; D K Turgeon; P Schmiedlin-Ren; M B Brown; W Guo; S J Rossi; L Z Benet; P B Watkins Journal: Clin Pharmacol Ther Date: 1997-09 Impact factor: 6.875
Authors: Harma Ellens; Shibing Deng; Joann Coleman; Joe Bentz; Mitchell E Taub; Isabelle Ragueneau-Majlessi; Sophie P Chung; Krisztina Herédi-Szabó; Sibylle Neuhoff; Johan Palm; Praveen Balimane; Lei Zhang; Masoud Jamei; Imad Hanna; Michael O'Connor; Dallas Bednarczyk; Malin Forsgard; Xiaoyan Chu; Christoph Funk; Ailan Guo; Kathleen M Hillgren; Libin Li; Anne Y Pak; Elke S Perloff; Ganesh Rajaraman; Laurent Salphati; Jan-Shiang Taur; Dietmar Weitz; Heleen M Wortelboer; Cindy Q Xia; Guangqing Xiao; Tetsuo Yamagata; Caroline A Lee Journal: Drug Metab Dispos Date: 2013-04-25 Impact factor: 3.922
Authors: X Chu; K Korzekwa; R Elsby; K Fenner; A Galetin; Y Lai; P Matsson; A Moss; S Nagar; G R Rosania; J P F Bai; J W Polli; Y Sugiyama; K L R Brouwer Journal: Clin Pharmacol Ther Date: 2013-04-10 Impact factor: 6.875
Authors: M J Zamek-Gliszczynski; C A Lee; A Poirier; J Bentz; X Chu; H Ellens; T Ishikawa; M Jamei; J C Kalvass; S Nagar; K S Pang; K Korzekwa; P W Swaan; M E Taub; P Zhao; A Galetin Journal: Clin Pharmacol Ther Date: 2013-02-25 Impact factor: 6.875