Biomedical Engineering Reference
In-Depth Information
Predictive relations are also developed for (a) the binding rate coefficient,
k
1
and
k
2
,foradual-
fractal analysis as a function of the bradykinin concentration (in nM) in solution (
Fang et al.,
2006
), (b) the affinity,
K
2
(
k
2
/
k
d
) as a function of the ratio of the fractal dimensions,
D
f2
/
D
fd
, present in the binding and the dissociation phases for the different bradykinin con-
centrations in solution in the 8-128 nM range (
Fang et al., 2006
), and (c) the binding rate coef-
ficient,
k
2
, as a function of the fractal dimension,
D
f2
, or the degree of heterogeneity present on
the sensor chip surface (
Fang et al., 2006
). In this case an eighth order of dependence is
exhibited, which indicates that the binding rate coefficient,
k
2
, is extremely sensitive to the
degree of heterogeneity that exists ob the biosensor chip surface. (d) The binding rate coeffi-
cient,
k
2
, exhibits a negative 10.783 order of dependence on the fractal dimension,
D
f2
,or
the degree of heterogeneity that exists on the biosensor chip surface for the binding of m
b
CD
cholesterol in solution to HeLa cells cultivated on a gold-coated prism (
Ziblat et al., 2006
), (e)
the binding rate coefficient,
k
1
and
k
2
, as a function of the stimulation frequency, in Hz, for the
binding and dissociation phases for the calcium-FRET-based calcium biosensor employing tro-
ponin C (
Mank et al., 2006
), and (f) the binding rate coefficient,
k
2
, as a function of the fractal
dimension,
D
f2
, or the degree of heterogeneity that exists on the sensor chip surface.
ΒΌ
The three different examples presented in this chapter emphasize that the degree of heteroge-
neity that exists on the biosensor surface does significantly affect, in general, the rate coeffi-
cient and affinity values, and subsequently the kinetics, in general. These are just a few of the
representative examples that are available in the literature. More such studies are required to
determine whether the binding and the dissociation rate coefficient(s), and subsequently the
affinity values are sensitive to their fractal dimensions present on the biosensor surface with
regard to these types of reactions.
References
Abraham V, DL Taylor, and JR Haskins, High content screening applied to large-scale cell biology,
Trends in
Biotechnology
,
22
, 15-22 (2004).
Blake RA, Cellular screening assays using fluorescence microscopy,
Current Opinions in Pharmacology
,
1
,
533-538 (2001).
Brand AH and N Perrimon, Targeted gene expression as a means of altering cell fates and generating phenotypes,
Development
,
118
, 401-415 (1993).
Corel Quattro Pro 8.0, Corel Corporation, Ottawa, Canada (1997).
Fang Y, AM Ferrie, and G Li, Probing cytoskeleton modulation by optical biosensors,
FEBS Letters
,
579
,
4175-4180 (2005a).
Fang Y, AM Ferrie, NH Fontaine, and PK Yuen, Characteristics of dynamic mass distribution of EGF receptor
signaling in living cells measured with label free optical biosensors,
Analytical Chemistry
,
77
, 5720-5725
(2005b).
Fang Y, G Li, and J Peng, Optical biosensor provides insights for bradykinin B
2
receptor signaling in A431 cells,
FEBS Letters
,
579
, 6365-6374 (2005c).
Fang Y, AM Ferrie, NH Fonatine, J Mauro, and J Balakrishnan, Resonant waveguide grating biosensor for living
cell biosensing,
Biophysical Journal
,
91
, 1925-1940 (2006).
