Use Excel Solver to find Vmax and Km., Study notes of MS Microsoft Excel skills

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Use Excel Solver to find Vmax and Km.

K S

S

V V

m

max

% Michaelis & Menten Model Fit.

% File name "SimpleMMplot.m".

clear

clf

global S V;

% experiemntal data

S=[0 1 2 3 4 5 6 7 8];

V=[0 0.08 0.15 0.18 0.2 0.21 0.215 0.216 0.216];

v0=[1; 1];

a=fminsearch('two_var',v0); %least square errors

Km=a(1);

Vmax=a(2);

Vmodel=Vmax*S./(Km+S);

plot(S,V,'ro', S, Vmodel)

xlabel('Concentrations')

ylabel('rate')

legend('Data','Predict')

function sumsqe= two_var(aa) global S V; Km =aa(1); Vmax =aa(2); Vmodel=VmaxS./(Km+S); err=V-Vmodel; err2=err.err; sumsqe=sum(err2); return K S S V V

m

max

% dynamic enzyme kinetics: filename "Enzymekinetics.m" %======================================================= clear clf global k1 k2 k3; % define rate constant, k3 is k1-minus. k1=100; k2=0.1; k3=100; % initial conditions S0=1; E0=1; ES0=0; P0=0; tend=100; y0=[S0 E0 ES0 P0]; [t,y]=ode45('MMmodel',[0 tend], y0); % results S=y(:,1); E=y(:,2); ES=y(:,3); P=y(:,4); subplot(211) plot (t, S, 'k', t, P, 'y'); title('Substrate vs Products'), xlabel('time'), ylabel('amount'), legend('substrate','product', 1); subplot(212) plot (t, E, 'k', t, ES, 'y'); title('Enzyme vs Enzyme complex'), xlabel('time'), ylabel('amount'), legend('Enzyme','Enzyme complex', 1);

% filename MMmodel.m, This function is used to % calculate the MM model using ODE % Initial conditions: y0=[S0 E0 ES0 P0] %*********************************************** function ydot=MMmodel(t,y) global k1 k2 k3; ydot(1)= -k1y(1)y(2)+k3y(3); %substrate ydot(2)= -k1y(1)y(2)+(k3+k2)y(3); %enzyme ydot(3)= k1y(1)y(2)-(k3+k2)y(3); %enzyme complex ydot(4)= k2y(3); % product ydot=ydot‘;