Validation of fractal-like kinetic models by time-resolved binding kinetics of dansylamide and carbonic anhydrase in crowded media

Biophysical Journal

Volumn 100, Issue 10, 2011, Pages 2495-2503

  Neff, Kevin L ^a   Offord, Chetan P ^a   Caride, Ariel J ^a   Strehler, Emanuel E ^a   Prendergast, Franklyn G ^a   Bajzer, Željko ^a  

^a MAYO CLINIC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79959667712     PISSN: 00063495     EISSN: 15420086     Source Type: Journal    
DOI: 10.1016/j.bpj.2011.04.016     Document Type: Article

References (51)

1. Minton, A. P. 1981. Excluded volume as a determinant of macromolecular structures and reactivity. Biopolymers. 20:2093-2120.
2. Zimmerman, S. B., and A. P. Minton. 1993. Macromolecular crowding: biochemical, biophysical, and physiological consequences. Annu. Rev. Biophys. Biomol. Struct. 22:27-65. (Pubitemid 23180316)
3. Minton, A. P. 2001. The influence of macromolecular crowding and macromolecular confinement on biochemical reactions in physiological media. J. Biol. Chem. 276:10577-10580. (Pubitemid 38089223)
4. Hall, D., and A. P. Minton. 2003. Macromolecular crowding: qualitative and semiquantitative successes, quantitative challenges. Biochim. Biophys. Acta. 1649:127-139. (Pubitemid 38234581)
5. Berry, H. 2002. Monte Carlo simulations of enzyme reactions in two dimensions: fractal kinetics and spatial segregation. Biophys. J. 83:1891-1901.
6. Turner, T. E., S. Schnell, and K. Burrage. 2004. Stochastic approaches for modelling in vivo reactions. Comput. Biol. Chem. 28:165-178.
7. Homchaudhuri, L., N. Sarma, and R. Swaminathan. 2006. Effect of crowding by dextrans and Ficolls on the rate of alkaline phosphatasecatalyzed hydrolysis: a size-dependent investigation. Biopolymers. 83:477-486. (Pubitemid 44851661)
8. Aranda, J. S., E. Salgado, and A. Muñoz-Diosdado. 2006. Multifractality in intracellular enzymatic reactions. J. Theor. Biol. 240:209-217.
9. Kozer, N., Y. Y. Kuttner, ..., G. Schreiber. 2007. Protein-protein association in polymer solutions: from dilute to semidilute to concentrated. Biophys. J. 92:2139-2149. (Pubitemid 46495275)
10. Sun, J., and H. Weinstein. 2007. Toward realistic modeling of dynamic processes in cell signaling: quantification of macromolecular crowding effects. J. Chem. Phys. 127:155105.
11. Grima, R., and S. Schnell. 2007. A mesoscopic simulation approach for modeling intracellular reactions. J. Stat. Phys. 128:139-164.
12. Dix, J. A., and A. S. Verkman. 2008. Crowding effects on diffusion in solutions and cells. Annu Rev Biophys. 37:247-263.
13. Agrawal, M., S. B. Santra, ..., R. Swaminathan. 2008. Effect of macromolecular crowding on the rate of diffusion-limited enzymatic reaction. Pramana. 71:359-368.
14. Phillip, Y., E. Sherman, ..., G. Schreiber. 2009. Common crowding agents have only a small effect on protein-protein interactions. Biophys. J. 97:875-885.
15. Elcock, A. H. 2010. Models of macromolecular crowding effects and the need for quantitative comparisons with experiment. Curr. Opin. Struct. Biol. 20:196-206.
16. Zhou, H. X., G. Rivas, and A. P. Minton. 2008. Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences. Annu Rev Biophys. 37:375-397.
17. Savageau, M. A. 1995. Michaelis-Menten mechanism reconsidered: implications of fractal kinetics. J. Theor. Biol. 176:115-124.
18. Savageau, M. A. 1998. Development of fractal kinetic theory for enzyme-catalysed reactions and implications for the design of biochemical pathways. Biosystems. 47:9-36. (Pubitemid 28369493)
19. Schnell, S., and T. E. Turner. 2004. Reaction kinetics in intracellular environments with macromolecular crowding: simulations and rate laws. Prog. Biophys. Mol. Biol. 85:235-260. (Pubitemid 38629911)
20. Grima, R., and S. Schnell. 2006. A systematic investigation of the rate laws valid in intracellular environments. Biophys. Chem. 124:1-10. (Pubitemid 44528094)
21. Bajzer, Ž., M. Huzak, ..., F. G Prendergast. 2006. Reaction kinetics in intracellular environments: the two proposed models yield qualitatively different predictions. Croat. Chem. Acta. 79:437 444.
22. Bajzer, Ž, M. Huzak, ..., F. G. Prendergast. 2008. Mathematical analysis of models for reaction kinetics in intracellular environments. Math. Biosci. 215:35-47.
23. Lindskog, S., P. Engerg, ..., L. Tibell. 1984. Kinetics and mechanism of carbonic anhydrase isoenzymes. In The Biology and Chemistry of the Carbonic Anhydrases. R. E. Tashian and D. Hewett-Emmett, editors. New York Academy of Sciences, New York. 61-75. (Pubitemid 14085830)
24. Day, Y S., C. L. Baird, ..., D. G. Myszka. 2002. Direct comparison of binding equilibrium, thermodynamic, and rate constants determined by surface-and solution-based biophysical methods. Protein Sci. 11:1017-1025. (Pubitemid 34441221)
25. Taylor, P. W., R. W. King, and A. S. Burgen. 1970. Kinetics of complex formation between human carbonic anhydrases and aromatic sulfonamides. Biochemistry. 9:2638-2645.
26. Klymko, P. W., and R. Kopelman. 1983. Fractal reaction kinetics: exciton fusion on clusters. J. Phys. Chem. 87:4565-4567.
27. Anacker, L. W., and R. Kopelman. 1984. Fractal chemical kinetics: simulations and experiments. J. Chem. Phys. 81:6402-6403.
28. Kopelman, R. 1986. Rate processes on fractals-theory, simulations and experiments. J. Stat. Phys. 42:185-200.
29. Kopelman, R. 1988. Fractal reaction kinetics. Science. 241:1620-1626.
30. Viscek, T 1989. Fractal Growth Phenomena. World Scientific, Singapore.
31. Li, H. Q., S. H. Chen, and H. M. Zhao. 1990. Fractal mechanisms for the allosteric effects of proteins and enzymes. Biophys. J. 58:1313-1320.
32. Szabo, A. 1991. Theoretical approaches to reversible diffusion-influenced reactions: monomer-excimer kinetics. J. Chem. Phys. 95:2481-2490.
33. Richards, P. M., and A. Szabo. 1991. Reversible trapping on a cubic lattice: comparison of theory and simulations. J. Stat. Phys. 65:1085-1093.
34. Savageau, M. A. 1970. Biochemical systems analysis. 3. Dynamic solutions using a power-law approximation. J. Theor. Biol. 26:215-226.
35. Voit, E. O., and M. A. Savageau. 1987. Accuracy of alternative representations for integrated biochemical systems. Biochemistry. 26:6869-6880.
36. Voit, E. O. 2000. Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists. Cambridge University Press, Cambridge.
37. Savageau, M. A. 1993. Influence of fractal kinetics on molecular recognition. J. Mol. Recognit. 6:149-157.
38. Voit, E. O. 2003. Biochemical and genomic regulation of the trehalose cycle in yeast: review of observations and canonical model analysis. J. Theor. Biol. 223:55-78. (Pubitemid 36627546)
39. Maki, Y., Y. Takahashi, ..., M. Okamoto. 2004. An integrated comprehensive workbench for inferring genetic networks: voyagene. J. Bioinform. Comput. Biol. 2:533-550. (Pubitemid 39295155)
40. Weber, G. 1952. Polarization of the fluorescence of macromolecules. I. Theory and experimental method. Biochem. J. 51:145-155.
41. Edelhoch, H. 1967. Spectroscopic determination of tryptophan and tyrosine in proteins. Biochemistry. 6:1948-1954.
42. Pace, C. N., F. Vajdos, ..., T. Gray. 1995. How to measure and predict the molar absorption coefficient of a protein. Protein Sci. 4:2411-2423.
43. Offord, C., and Z. Bajzer. 2001. A hybrid global optimization algorithm involving simplex and inductive search. Lect. Notes Comput. Sci. 2074:680-688. (Pubitemid 33285632)
44. Bevington, P. R., and D. K. Robinson. 2003. Data Reduction and Error Analysis for the Physical Sciences. McGraw-Hill, Boston.
45. Press, W. H., S. A. Teukolsky, ..., B. P. Flannery. 1992. Numerical Recipes. Cambridge University Press, Cambridge.
46. Davidian, M., and A. R. Gallant. 1993. The nonlinear mixed effects model with a smooth random effects density. Biometrika. 80:475-488.
47. Buckwitz, D., and H. G. Holzhütter. 1990. A new method to discriminate between enzyme-kinetic models. Comput. Math. Appl. 20:117-126.
48. Bajzer, Ž., M. C. Moncrieffe, ..., F. G. Prendergast. 2001. Complex homogeneous and heterogeneous fluorescence anisotropy decays: enhancing analysis accuracy. Biophys. J. 81:1765-1775. (Pubitemid 32783612)
49. Zwanzig, S. 1980. The choice of approximative models in nonlinear regression. Statistics. 11:23-47.
50. Goutsias, J. 2007. Classical versus stochastic kinetics modeling of biochemical reaction systems. Biophys. J. 92:2350-2365. (Pubitemid 46536418)
51. Andrews, S. S., and D. Bray. 2004. Stochastic simulation of chemical reactions with spatial resolution and single molecule detail. Phys. Biol. 1:137-151. (Pubitemid 44362291)