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Team:Fatih-Medical/Sherlocoli/Modelling
From 2012.igem.org
As Fatih Medical team we aim to make Cancer diagnosis by means of bacteria and Circulating Tumor Cells (CTC) interaction. CTCs have exceeded Epithelial Cell Adhesion Molecules (EpCam) on their cell membranes. On EpCam surface there are a lot of binding sites; identifying these binding sites we searched for anti-EpCams and found out that the most appropriate is C215 so we decide to operate with C215. In order to activate system that we used in Cancer Detection Module the Outer Membrane Protein A (OmpA) must be dimerized therefore we will use two binding sites on EpCam surface. (Figure 1)
Figure 1
When EpCam binds to the C215 that attached to the OmpA Sherlocoli will catch CTC thereby trigger activation of system and start module work. (Figure 2)
Figure 2
Because of our team consists of only medical students we didn’t have any experience in modeling but thanks to some team members who worked with MATLAB SİMBİOLOGY program and could make rational equations finally we have our modeling. After analyzing EpCam anti-EpCam interactions from different articles[1] we’ve reached to the related data that characterise it. (table 1)
Determination of kinetic constants for antibody-EpCAM interactions:
Reaction kinetics:
After transforming the diagram from figure2 into the equation we get the following equation system;
One anti-Epcam C binds to one of two binding side of Epcam protein EE with rate kon or a anti Epcam-Binding sides CEE dissociates with koff
The second anti Epcam C binds to the a anti Epcam-Binding sides CEE with rate kdon or the dimer CEEC dissociates in one anti Epcam C and one anti Epcam- Binding sides CEE with rate kdoff:
When two anti-EpCam become dimerized consequently OmpA binded to EpCam dimerized too thus activating the system with Ka rate.
When equations above are entered to the program with their reaction rates we get the following graph;
Matlab.m file
MATLAB M FİLE CODE
‘’function createfigure(X1, YMatrix1)
%CREATEFIGURE(X1,YMATRIX1)
% X1: vector of x data
% YMATRIX1: matrix of y data
% Auto-generated by MATLAB on 22-Sep-2012 18:56:18
% Create figure
figure1 = figure('NumberTitle','off','Name','Time - Figure 1');
% Create axes
axes1 = axes('Parent',figure1);
box(axes1,'on');
hold(axes1,'all');
% Create multiple lines using matrix input to plot
plot1 = plot(X1,YMatrix1,'Parent',axes1);
set(plot1(1),'DisplayName','C');
set(plot1(2),'DisplayName','EE');
set(plot1(3),'DisplayName','CEE');
set(plot1(4),'DisplayName','CEEC');
set(plot1(5),'DisplayName','2A');
% Create xlabel
xlabel({'Time'});
% Create ylabel
ylabel('States');
% Create title
title('States versus Time');
% Create legend
legend1 = legend(axes1,'show');
set(legend1,'Interpreter','none',...
'Position',[0.0137053352912308 0.753271028037372 0.0690161527165932 0.183177570093458]);’’
References:
1 P Ruf*,1, O Gires2, M Ja¨ger1, K Fellinger2,5, J Atz3 and H Lindhofer1,4 1Department of Antibody Development, TRION Research GmbH, Martinsried, Germany; 2Clinical Cooperation Group Molecular Oncology, GSF-Research Centre for Health, and Environment and Department of Otorhinolaryngology, Ludwig-Maximilians-University, Munich, Germany; 3Department of Preclinical Research and Development, Fresenius Biotech GmbH, Gra¨felf ing, Germany; 4CEO, TRION Pharma GmbH, Munich, Germany ’’Characterisation of the new EpCAM-specific antibody HO-3: implications for trifunctional antibody immunotherapy of cancer’’
