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Proper quantification of simulator dynamics, max motor per end = 1 vs multiple motors per end

Max 1 motor per end

rng('default');%initialize RNG for reproducibility
%choose params which support stable tug of war, ie
% high native processivity, low PG unbinding rate eps0<< koff0
% frequent PG binding, pi0>> kOn0
% otherwise based on experimental data rates
motorState.kOn0 = 0.5/60; %rate of single motor (synthase) binding to cargo (mreB) (From Stu data)
motorState.pi0 =10*motorState.kOn0; %single motor binding rate s^-1 %promotes tug of war
motorState.eps0=0.3/60;%single motor unbinding rate s^-1 %promotes tug of war, also at low concentration 
% derived from Stu data)
%processivity is synthesis limited
motorState.kOff0 = 10*motorState.eps0; %rate of single motor (synthase) unbinding from cargo (mreB)
motorState.Fdetach = 1;%detachment force pN nm
motorState.Fstall = 100; %stall force pN nM
motorState.vF=40;%forward velocity nm/s
motorState.vB=0.1;%backward velocity nm/s
motorState.Nplus=0;%initial total number of plus motors 
motorState.Nminus=0;%initial total number of bound plus motors 
motorState.nPlus=0;%number of bound plus motors 
motorState.nMinus=0;%number of bound minus motors
simPar.nStep= 100;
simPar.doFixedTime=true;
simPar.simTime = 5000;

%Nmax = 1 each side (max number of motors), low concentration, which should give frequent pausing model

motorState.Nmax = 1;

motorState.motorConcentration =0.1;%arb units, essentiall scaling of low synthase concentration data here

[dynamics] = lipowskiWithUnbindingSim(motorState,simPar);

t=dynamics.t;

x=dynamics.x;

figure;

plot(t,x);

ylabel('Displacement (nm)');

xlabel('Time (s)');

%Nmax = 1 each side, high concentration, which should give frequent reversals

motorState.Nmax = 1;

motorState.motorConcentration =10;%arb units, essentiall scaling of low synthase concentration data here

[dynamics] = lipowskiWithUnbindingSim(motorState,simPar);

t=dynamics.t;

x=dynamics.x;

figure;

plot(t,x);

ylabel('Displacement (nm)');

xlabel('Time (s)');

%Nmax = inf each side, low concentration which should give frequent pausing

motorState.Nmax = inf;

motorState.motorConcentration =0.1;%arb units, essentiall scaling of low synthase concentration data here

[dynamics] = lipowskiWithUnbindingSim(motorState,simPar);

t=dynamics.t;

x=dynamics.x;

figure;

plot(t,x);

ylabel('Displacement (nm)');

xlabel('Time (s)');

%Nmax = inf each side, high concentration which lipowski predicts should give

%infrequent pausing, relatively infrequent reversals but high processivity

motorState.Nmax = inf;

motorState.motorConcentration =10;%arb units, essentiall scaling of low synthase concentration data here

[dynamics] = lipowskiWithUnbindingSim(motorState,simPar);

t=dynamics.t;

x=dynamics.x;

figure;

plot(t,x);

ylabel('Displacement (nm)');

xlabel('Time (s)');

%Nmax = inf each side, intermediate concentration which lipowski should

%give some tug of war

motorState.Nmax = inf;

motorState.motorConcentration =1;%arb units, essentiall scaling of low synthase concentration data here

[dynamics] = lipowskiWithUnbindingSim(motorState,simPar);

t=dynamics.t;

x=dynamics.x;

figure;

plot(t,x);

ylabel('Displacement (nm)');

xlabel('Time (s)');

%and again

motorState.Nmax = inf;

motorState.motorConcentration =1;%arb units, essentiall scaling of low synthase concentration data here

[dynamics] = lipowskiWithUnbindingSim(motorState,simPar);

t=dynamics.t;

x=dynamics.x;

figure;

plot(t,x);

ylabel('Displacement (nm)');

xlabel('Time (s)');

initial rates etc analysis

motorConcRange = 10.^(0:4).*0.01
motorConcRange = 1×5
    0.0100    0.1000    1.0000   10.0000  100.0000
analysisPar.frameInterval = 6;
analysisPar.zeroSpeedThresh = 5;
analysisPar.switchTooCloseThresh = 4;
nSimRepeat=100
nSimRepeat = 100

Max motor = 1

motorState.Nmax = 1;
for ii = 1:numel(motorConcRange)
    motorState.motorConcentration =motorConcRange(ii);
    [processivityNmax1{ii}, speedNmax1{ii}, lifetimeNmax1{ii}, rateNmax1{ii}, fractionMotileNmax1(ii,:), simResultNmax1{ii},NmotorNmax1{ii}] =...
     quantifySimDynamics(motorState, simPar,analysisPar,nSimRepeat);
   lifetimeAllNmax1{ii} = lifetimeNmax1{ii}.All;
   lifetimeProcessiveNmax1{ii} = lifetimeNmax1{ii}.Processive;
   lifetimeStaticNmax1{ii} = lifetimeNmax1{ii}.Static;
end
%make the plots
fieldName={'c1','c2','c3','c4','c5'};
%categoryName={'10^-2', '10^-1','10^0','10^1','10^2'};
categoryName={'10^0', '10^1','10^2','10^3','10^4'};

figure;

violinplot(cell2struct(processivityNmax1,fieldName,2));

xlabel('Relative synthase concentration');

ylabel('Processivity (nm)');

hA=gca;

hA.XTickLabel=categoryName;

%probably dont expect speed to be affected based on current sim parameters

figure;

violinplot(cell2struct(speedNmax1,fieldName,2));

xlabel('Relative synthase concentration');

ylabel('Speed (nm/s)');

hA=gca;

hA.XTickLabel=categoryName;

Well that's me surprised then I guess

%total lifetime

figure;

violinplot(cell2struct(lifetimeAllNmax1,fieldName,2));

xlabel('Relative synthase concentration');

ylabel('All lifetime (s)');

ylim([0 10e3])

hA=gca;

hA.XTickLabel=categoryName;

%processive lifetime

figure;

violinplot(cell2struct(lifetimeProcessiveNmax1,fieldName,2));

xlabel('Relative synthase concentration');

ylabel('Processive lifetime (s)');

hA=gca;

hA.XTickLabel=categoryName;

%static lifetime

figure;

violinplot(cell2struct(lifetimeStaticNmax1,fieldName,2));

xlabel('Relative synthase concentration');

ylabel('Static lifetime (s)');

ylim([0 20e3])

hA=gca;

hA.XTickLabel=categoryName;

%rates

for ii = 1:numel(motorConcRange)

pause_processive(ii,:) = rateNmax1{ii}.pause_processive;

reversal_processive(ii,:) = rateNmax1{ii}.reversal_processive;

staticToMotile(ii,:) = rateNmax1{ii}.staticToMotile;

end

figure;

hold all;

errorbar(motorConcRange*1e2, pause_processive(:,1),...

pause_processive(:,1)-pause_processive(:,2),pause_processive(:,3)-pause_processive(:,1));

errorbar(motorConcRange*1e2, reversal_processive(:,1),...

reversal_processive(:,1)-reversal_processive(:,2),reversal_processive(:,3)-reversal_processive(:,1));

errorbar(motorConcRange*1e2, staticToMotile(:,1),...

staticToMotile(:,1)-staticToMotile(:,2),staticToMotile(:,3)-staticToMotile(:,1));

hA=gca;

hA.XScale='log';

legend('Pausing','Reversal','Paused to motile');

xlabel('Relative synthase concentration');

ylabel('Rate (s^{-1})')

%faction motile v static

figure;

errorbar(motorConcRange*1e2, fractionMotileNmax1(:,1),...

fractionMotileNmax1(:,1)-fractionMotileNmax1(:,2),fractionMotileNmax1(:,3)-fractionMotileNmax1(:,1));

hA=gca;

hA.XScale='log';

xlabel('Relative synthase concentration');

ylabel('Motile fraction')

%motor loading

figure;

violinplot(cell2struct(NmotorNmax1,fieldName,2));

hA=gca;

hA.XScale='log';

hA.XTickLabel=categoryName;

xlabel('Relative synthase concentration');

ylabel('Bound motors')

Max motor = inf

motorState.Nmax = inf;
for ii = 1:numel(motorConcRange)
    motorState.motorConcentration =motorConcRange(ii);
    [processivityNmaxInf{ii}, speedNmaxInf{ii}, lifetimeNmaxInf{ii}, rateNmaxInf{ii}, fractionMotileNmaxInf(ii,:), simResultNmaxInf{ii}, NmotorNmaxInf{ii}] =...
     quantifySimDynamics(motorState, simPar,analysisPar,nSimRepeat);
   lifetimeAllNmaxInf{ii} = lifetimeNmaxInf{ii}.All;
   lifetimeProcessiveNmaxInf{ii} = lifetimeNmaxInf{ii}.Processive;
   lifetimeStaticNmaxInf{ii} = lifetimeNmaxInf{ii}.Static;
end

%make the plots

fieldName={'c1','c2','c3','c4','c5'};

%categoryName={'10^-2', '10^-1','10^0','10^1','10^2'};

categoryName={'10^0', '10^1','10^2','10^3','10^4'};

figure;

violinplot(cell2struct(processivityNmaxInf,fieldName,2));

xlabel('Relative synthase concentration');

ylabel('Processivity (nm)');

hA=gca;

hA.XTickLabel=categoryName;

%probably dont expect speed to be affected based on current sim parameters

figure;

violinplot(cell2struct(speedNmaxInf,fieldName,2));

hA=gca;

hA.XTickLabel=categoryName;

xlabel('Relative synthase concentration');

ylabel('Speed (nm/s)');

%total lifetime

figure;

violinplot(cell2struct(lifetimeAllNmaxInf,fieldName,2));

xlabel('Relative synthase concentration');

ylabel('All lifetime (s)');

ylim([0 10e3])

hA=gca;

hA.XTickLabel=categoryName;

%processive lifetime

figure;

violinplot(cell2struct(lifetimeProcessiveNmaxInf,fieldName,2));

xlabel('Relative synthase concentration');

ylabel('Processive lifetime (s)');

hA=gca;

hA.XTickLabel=categoryName;

% %static lifetime

% figure;

% violinplot(cell2struct(lifetimeStaticNmaxInf,fieldName,2));

% xlabel('Relative synthase concentration');

% ylabel('Static lifetime (s)');

% ylim([0 20e3])

%rates

for ii = 1:numel(motorConcRange)

pause_processive(ii,:) = rateNmaxInf{ii}.pause_processive;

reversal_processive(ii,:) = rateNmaxInf{ii}.reversal_processive;

staticToMotile(ii,:) = rateNmaxInf{ii}.staticToMotile;

end

figure;

hold all;

errorbar(motorConcRange*1e2, pause_processive(:,1),...

pause_processive(:,1)-pause_processive(:,2),pause_processive(:,3)-pause_processive(:,1));

errorbar(motorConcRange*1e2, reversal_processive(:,1),...

reversal_processive(:,1)-reversal_processive(:,2),reversal_processive(:,3)-reversal_processive(:,1));

hA=gca;

hA.XScale='log';

legend('Pausing','Reversal');

xlabel('Relative synthase concentration');

ylabel('Rate (s^{-1})')

figure;

errorbar(motorConcRange*1e2, staticToMotile(:,1),...

staticToMotile(:,1)-staticToMotile(:,2),staticToMotile(:,3)-staticToMotile(:,1));

hA=gca;

hA.XScale='log';

title('Paused to motile')

xlabel('Relative synthase concentration');

ylabel('Rate (s^{-1})')

%faction motile v static

figure;

errorbar(motorConcRange*1e2, fractionMotileNmaxInf(:,1),...

fractionMotileNmaxInf(:,1)-fractionMotileNmaxInf(:,2),fractionMotileNmaxInf(:,3)-fractionMotileNmaxInf(:,1));

hA=gca;

hA.XScale='log';

xlabel('Relative synthase concentration');

ylabel('Motile fraction')

%motor loading

figure;

violinplot(cell2struct(NmotorNmaxInf,fieldName,2));

hA=gca;

hA.YScale='log';

hA.YGrid='on';

xlabel('Relative synthase concentration');

ylabel('Bound motors')

hA.XTickLabel=categoryName;

save('lipowskiSimInitialResults220310.mat')

Warning: Figure is saved in lipowskiSimInitialResults220310.mat. Saving graphics handle variables can cause the creation of very large files. To save graphics figures, use savefig.

%rates

for ii = 1:numel(motorConcRange)

pause_processive1(ii,:) = rateNmax1{ii}.pause_processive;

reversal_processive1(ii,:) = rateNmax1{ii}.reversal_processive;

staticToMotile1(ii,:) = rateNmax1{ii}.staticToMotile;

end

figure;

hold all;

errorbar(motorConcRange*1e2, reversal_processive1(:,1),...

reversal_processive1(:,1)-reversal_processive1(:,2),reversal_processive1(:,3)-reversal_processive1(:,1));

errorbar(motorConcRange*1e2, reversal_processive(:,1),...

reversal_processive(:,1)-reversal_processive(:,2),reversal_processive(:,3)-reversal_processive(:,1));

hA=gca;

hA.XScale='log';

legend('Nmax=1','Nmax=inf');

xlabel('Relative synthase concentration');

ylabel('Reversal rate (s^{-1})')