In order to evaluate the flavonoids degradation ability of FLR enzyme, we conducted the enzyme activity testsby using 4 kinds of flavonoids samples: apigenin, chrysin, luteolin, diosmetin, repectively.
Following is the data we collected during the tests:
We designed to build models to forecast the degradation rate of our FLR enzyme by time for different flavonoids samples. Therefore, we chose the appropriate equation to fit these points by Matlab.
Since these curves seem all decline trends and there are not many points yet, we chose to adopt the following negative exponential function to prevent the negative value of the concentration:
And its analytic expression will be:
According to the modeling results for each samples showing below, the fitting degrees are the same, 1.
a
b
c
d
Figure 2. The fitting curves of apigenin(a), chrysin(b), luteolin(c), diosmetin(d)
As seen above (figure 2), these 4 curves present very similar trends and these functions could be served as a reference to forecast the duration of how our FLR enzyme achieves its efficiency if we could settle the recommending degradation ratio of the flavonoids. For example, for chrysin, it might take 1 hour around for the FLR enzyme to degrade the half.
Besides, we also took the derivative of these curves to analyze their degradation rate by hours.
Figure 3. The curves of the degradation rate against hours for apigenin, chrysin, luteolin, diosmetin
In figure 3, it indicates that the degradation rate for diosmetin is much faster than the other three during the first 2 hours but it immediately goes to flatten out. It might be related to the concentration of the substrate (diosmetin) which means that the FLR enzyme would be very suitable for the degradation of high concentration flavonoids (diosmetin).