Computational Modeling of Complex Reactions Kinetics in Biosensors ; Kompiuterinis daugiapakopių reakcijų kinetikos biojutikliuose modeliavimas

Sujets

• Biosensor
• Computer simulation
• Informatics

Informations

• Publié par: vilnius_university
• Publié le: 01 janvier 2011
• Nombre de lectures: 9
• Langue: English
• Poids de l'ouvrage: 2 Mo

Extrait

VILNIUSUNIVERSITY
˙EvelinaGaidamauskaite
COMPUTATIONALMODELINGOFCOMPLEXREACTIONSKINETICSIN
BIOSENSORS
Doctoraldissertation
Physicalsciences,informatics(09P)
Vilnius,2011Theworkwasperformedin2006-2011attheVilniusUniversity.
Scientificsupervisor:
prof. dr. Romas Baronas (Vilnius University, physical sciences, informatics -
09P)VILNIAUSUNIVERSITETAS
EvelinaGaidamauskaite˙
KOMPIUTERINISDAUGIAPAKOPIU˛REAKCIJU˛KINETIKOS
BIOJUTIKLIUOSEMODELIAVIMAS
Daktarodisertacija
Fiziniaimokslai,informatika (09P)
Vilnius,2011Disertacijarengta2006-2011metaisVilniausuniversitete.
Mokslinisvadovas:
prof. dr. RomasBaronas(Vilniausuniversitetas, fiziniaimokslai, informatika -
09P)Acknowledgements
FinancialsupportfromtheTheStateStudiesFoundationandresearchprojects:
"Development of bioelectrocatalysis for synthesis and analysis (BIOSA)" fun-
ded by the grant (No. PBT-04/2010) from the Research Council of Lithuania
and "Developing computational techniques, algorithms and tools for efficient
simulationandoptimizationofbiosensorsofcomplexgeometry"fundedbythe
EuropeanSocialFundunderMeasureVP1-3.1-ŠMM-07-K"SupporttoResearch
ofScientistsandOtherResearchers(GlobalGrant)"isgratefullyacknowledged.
Letmeexpressmygratitudetothepeoplewhohavehelpedmeinmanyways.
My first words of gratitude are due to my supervisor, prof. Romas Baronas,
for introducing me to the problem of numerical modeling of biosensors, for
academic guidance and for the invaluable patience over these last years. It is
anhonorformetothankprof. JuozasKulysfromtheInstituteofBiochemistry
forchallengingdiscussions.
I have also received a lot of care and support from my family. Among them,
specialthanks tomy brothers Ervinas Gaidamauskasfor profound support on
Biochemistry, Erikas Gaidamauskas for the help throughout the process, and
Eduardas Gaidamauskas for challenging me to fulfill my potential. I heartily
thank my parents, Dalia and Sergejus. They raised me, taught me, and sup-
ported me. Andof course to Aleksandras,thanks for the incredible amount of
patienceyouhadwithmeinthelastmonths.
EvelinaGaidamauskaite˙
Vilnius
26thSeptember2011
vTableofContents
NotationandAcronyms viii
Introduction 1
ResearchObject . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
ResearchMethodology . . . . . . . . . . . . . . . . . . . . . . . . . 3
StatementoftheProblemandTasks . . . . . . . . . . . . . . . . . 3
Scientific NoveltyandResults . . . . . . . . . . . . . . . . . . . . . 4
PracticalSignificance . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Statements PromotedtoDefend . . . . . . . . . . . . . . . . . . . . 5
ReliabilityoftheResults . . . . . . . . . . . . . . . . . . . . . . . . 6
ApprovaloftheResults . . . . . . . . . . . . . . . . . . . . . . . . 6
Structure oftheThesis . . . . . . . . . . . . . . . . . . . . . . . . . 8
1 TheoreticalFramework 9
1.1 ClassificationofBiosensorsAccordingtoBioreceptor System . . . 10
1.1.1 Enzymebiosensors . . . . . . . . . . . . . . . . . . . . . . . 10
1.1.2 Antibody-antigenbiosensors . . . . . . . . . . . . . . . . . 11
1.1.3 DNA/RNAbiosensors . . . . . . . . . . . . . . . . . . . . . 13
1.2 ClassificationofBiosensorsAccordingtoTrasducer . . . . . . . . 14
1.2.1 Electrochemicalenzymebiosensors . . . . . . . . . . . . . 14
1.2.2 Opticalenzymebiosensors . . . . . . . . . . . . . . . . . . 16
1.3 EnzymeKinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.4 Diffusion Equation . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.5 Reaction-DiffusionEquation . . . . . . . . . . . . . . . . . . . . . 21
1.6 NumericalApproachesofEnzymeKineticsModeling . . . . . . . 22
1.6.1 Finitedifferencemethod . . . . . . . . . . . . . . . . . . . . 22
1.6.2 Tridiagonalmatrixalgorithm . . . . . . . . . . . . . . . . . 26
1.7 ComputationalModelingofBiosensors . . . . . . . . . . . . . . . 28
1.7.1 Modelrepresentation . . . . . . . . . . . . . . . . . . . . . . 28
1.7.2 Modelgeneration . . . . . . . . . . . . . . . . . . . . . . . . 30
1.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
viTABLEOFCONTENTS
2 MathematicalModelsofMulti-StepBiosensors 33
2.1 Peroxidase-basedOpticalBiosensor . . . . . . . . . . . . . . . . . 33
2.1.1 Modelingbiosensor . . . . . . . . . . . . . . . . . . . . . . 34
2.1.2 Mathematicalmodel . . . . . . . . . . . . . . . . . . . . . . 35
2.2 Laccase-basedSynergistic Biosensor . . . . . . . . . . . . . . . . . 41
2.2.1 Modelingbiosensor . . . . . . . . . . . . . . . . . . . . . . 42
2.2.2 Mathematicalmodel . . . . . . . . . . . . . . . . . . . . . . 44
2.3 Conclussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3 AutomatedModelingofMulti-stepBiosensors 50
3.1 ComputationalSchemesforModelingofBiosensors . . . . . . . . 50
3.1.1 Mathematicalmodel . . . . . . . . . . . . . . . . . . . . . . 51
3.1.2 Solution oftheproblem . . . . . . . . . . . . . . . . . . . . 53
3.1.3 Resultsanddiscussion . . . . . . . . . . . . . . . . . . . . . 59
3.2 ToolforAutomatedModelDevelopment . . . . . . . . . . . . . . 63
3.2.1 Modelrepresentation language . . . . . . . . . . . . . . . . 63
3.2.2 Generationofsimulator . . . . . . . . . . . . . . . . . . . . 67
3.2.3 Graphicaluserinterface . . . . . . . . . . . . . . . . . . . . 70
3.2.4 Software architecture . . . . . . . . . . . . . . . . . . . . . . 72
3.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4 ComputationalModelingofMulti-stepBiosensors 75
4.1 ComputationalModelingofPeroxidase-basedOpticalBiosensor . 76
4.1.1 Digitalsimulation . . . . . . . . . . . . . . . . . . . . . . . 76
4.1.2 Resultsanddiscussion: Absorbancebiosensor . . . . . . . 79
4.1.3 Resultsanddiscussion: Fluorescent biosensor . . . . . . . 92
4.2 ComputationalModelingofLaccase-basedSynergetic Biosensor . 96
4.2.1 Digitalsimulation . . . . . . . . . . . . . . . . . . . . . . . 96
4.2.2 Resultsanddiscussion . . . . . . . . . . . . . . . . . . . . . 97
4.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Conclusions 106
PublicationsbytheAuthor 108
Bibliography 110
CurriculumVitae 125
viiNotationandAcronyms
a boundaryofthei-thlayeri
A geometricalsurfaceoftheelectrode
A absorbance
A steadystateabsorbance∞
A steadystateabsorbancecalculatedatthemomentTR R
Bi Biotnumber
B dimensionlesssensitivity ofthebiosensorS
cmpI compoundI
C concentration ofC
d thicknessoftheenzymelayer
D diffusioncoefficient
D diffusioncoefficientofsubstanceQQ
E enzyme
ES enzyme-substratecomplex
E oxidizedformofenzymeox
E reducedformofenzymered
E concentration oftheenzyme
E relativeerrorr
E concentration oftheoxidizedenzymeinthei-thlayerox,i
E concentration ofthereducedenzymeinthei-thlayerred,i
E initialconcentration oftheenzyme0
ES concentration oftheenzyme-substratecomplex
F Faradayconstant
F(t) measuredfluorescence
F intensityoffluorescenceI
3−Fe(CN) hexacyanoferrate(III)(ferricyanide)6
4−Fe(CN) hexacyanoferrate(II)(ferrocyanide)6
viiiNotation andAcronyms
h meshsizeinthexdirection
+H hydrogenion
H O water2
H O hydrogenperoxide2 2
H concentration ofthehydrogenperoxideinthediffusionlayerb
H concentration ofthehydrogenperoxideintheenzymelayere
H hydrogenperoxideconcentration inthebulksolution0
I electriccurrent
I intensityofexcitation light0
I steadystatecurrentcalculatedatthemomentTR R
I steadystatecurrentbeforetheadditionofthemediator0R
I synergistic currentS
I steadystatecurrent∞
j diffusionfluxdensity
J densityofthecurrent
J densityofthesteadystatecurrent(atS ≫K )g 0 M
J densityofthesteadystatecurrent(atS ≪K )l 0 M
J densityofthesteadystatecurrentp
J densityofthesteadystatecurrentcalculatedatthemomentTR R
k i-threactionrateconstanti
K MichaelisconstantM
l effectivethickness oftheenzymelayerandNernstlayeref
Laccase(ox) oxidizedformoflaccase
Laccase(red) reducedformoflaccase
M numberofmeshintervalsonthet-axis
M oxidizedmediatorox
M reducedmediatorred
n numberofelectrons involvedinchargetransfere
N numberofmeshintervalsonthex-axis
O oxygen(O )2
O oxygenconcentration inthei-thlayeri
O initialconcentration oftheoxygen0
P product
P i-thproducti
P concentration oftheproduct
ixNotation and Acronyms
P concentration oftheproduct inthediffusionlayerb
P concentration oftheproduct intheenzymelayere
P concentration ofthei-thproductinthej-thlayeri,j
RDF resourcedescriptionframework
S substrate
S i-thsubstratei
S concentration ofthesubstrate
S concentration ofthesubstrate inthediffusionlayerb
S concentration ofthesubstrate intheenzymelayere
S concentration ofthei-thsubstrateinthej-thlayeri,j
S concentration ofsubstrate inthebulksolution0
S concentration ofi-thsubstrateinthebulksolutioni,0
SBML SystemsBiologyMarkupLanguage
SBGN SystemsBiologyGraphicalNotation
t timeaxiscoordinate
T durationoftheprocessanalysis
T momentthesteadystatewasreachedR
T computationtimerequiredtoachieverelativeerrorlimitE
u(x,t) unknownfunctionofthecontinuous arguments
ju unknownfunctionofthediscreteargumentsi
v reactionrate
V maximumreactionratemax
x spaceaxiscoordinate
XML ExtensibleMarkupLanguage
Greekletters