Modeling
In this part, we can construct a model diagram between the activity of the enzyme solution CCxynA and xylan concentration. It can be used to predict the activity of the enzyme solution CCxynA. The concentrations of xylan solution were 14uL, 70uL and 350uL, respectively. Table 1 shows the experimental data of the activity of CCxynA and xylan concentration.
Table 1.The experimental data of the activity of CCxynA and xylan concentration
Xylan concentration 14uL 70uL 350uL
ccxynA 0.225927521 0.381960253 0.534383396
Here, we establish differential equations ( 1 )
—   =   —(1)
Solved (2)： y = aln(bx) + c；
Where a,b and c is the parameter.
Substituting data to fit three parameter values.
Coding
    
      clear;clc;
      x0=[14 70 350];
      y0=[0.225927521 0.381960253 0.534383396];
      yy=@(a,t)a(1)*log(a(2)*t)+a(3)
      a0=[0.0001 0.0001 0.0001];
      a=nlinfit(x0,y0,yy,a0)
      x=[0:400];
      y=yy(a,x);
      plot(x0,y0,'b*',x,y,'r','linewidth',2')
      a=0.0958, b=0.0370, c=0.2896.
Model Results：
1.Activity of enzyme solution CCxynA
Figure.1 Model of CCxynA activity and xylan solution concentration
Conclusion
With the increase of xylan concentration, the model showed a trend of increasing first and then stabilizing. We can use this model to predict the maximum absorption rate (Vmax) and Michaelis constant (Km) of the enzyme solution CCxynA, thereby predicting the reaction rate and maximum activity of the enzyme.