1
Cita● on:Mlmowsk P,Carter TO,Weber OF(2013)Enzyme Cata ysis and he Outcome ons U P,oteonics B:o nform 6 141 doi:10 417211pb 1000271 to allect outcome by turning periodic subslrate inp!t into fl on-periodic prodr.rct generetion has been uncertain. Enamples were found in the (xidase peroxidase reaction J6] and a hemin hydrogen perodde- suirtite model of.atal)$is [7], bul broad potential for non-linearity in other emyme-calallzed systems has not been established. Enzlrnatic reactions.an be described in general tenns by a set of ordinary differential equatioDs for aII reactants (Figure 1). Thek format has some resernblance to the differential equations descrihing the t,orellz and Rdssler systems ofr}on-lillear dFami.s [8,9], and therelore implies the ?otential to generate cotupiex, possibly chaodc bchavior. Here we test the h,lothesis that eru,)lnc calallsis can affcct the outcome of biochemicxl reactions We investigate the panmeter space for the rate aonstants in substrate-activated and general enzlme catalysis, and we $tudy enzynre calalysis in a brarched reaction wirl tr,o competing arms. Materials and Methods L sirico modeling 'Ihe chemical reactioos under study can bc dcfined as sets of ordioary dillerential equations (ODLS) thal describe t})e rate ofchange of each reactant per time step- TIre soluiions oftllose equations show constant, peaiodiq ol non-periodic flow over time- Here, a solver ftom tr SciPy [t0] package (scipy.intcgrate.odeint) was used to model en4ane catal)sis. To solve the equations under study, the time step was sct to 0.01 seconds, resulting in a samp[ng frequency of 100 Hz. 'Ihe inpui fluctuated at a constani rate of0.01 l{2, i.e. each oscil}atioo took 100 seconds or 10000 points. A double precision arilhmetic (64 bit) was applied Non-lir€ar systcrns can be rcpresented in a hifurcation diagram as a set of densely packed poirts- the use of a Fourier transform Bives another method of visualization. lhe Fourier hansfbrm is a sigral represe$ation in a liequency space. Wlrereas a siglal in t-he time domain shous how much energy is carried in a given time period tLe Fourier spectrum shows how 1i!_h energy is carried in a given frequency range. 'Ihe periodicity of a siglal is particularly well represented on a Fourier spectrum-a-s a peak at a spediic frequency (and at ha Donic frequencies). Because in the chaos regime every period is presenl, the Irourier spectnfil of a chaotic signal has pealc for every frequencp A bilurcation djagram is a graphical method of presefltilrg a change itl a dyiamical s]Btcm depending on a change in one of the undcrlying parameters. A biiurcation plot represents a map, not a flow (the q itcm is representcd by a recurrencq not difierential, equation). If a system has oriy fixed pofurts in sofle parameter rarge, this should be rcprose[ted on the diagram a5 a solid [ine. Limit cycles are represented as nrultiple, vertical lines. The number of lines depends on the peiiod of oscillations. Chaos in this case is represented as a block of densely packed points. lo define the reaction states of the enz)'rne catallsis, we generxted bjfurcatioB maps by solving the sel of differential equations (Figure 2) fbr each of its parameters At every ite.alion,local minima and maxima qlues of a chosen variable v.ere plotted on a vertjcal a.xis. Upon completion of lhe desired range o[ parameters, the resulting graph pres€nts the change of the system's variables depending on the delrcd parameter change. Agent-based modeling For agent based modeling, a basic Netlrgo model on enzymc kineli.s was cdiied to allow for contjnuous rh)4llmic substrate input B dE=(峰 +k,)(IEtl lFl)一 kl:E]ISI― k41E〕 111 dt dES・ kl l【 ]lS〕 4[E]【 P〕(k2+k3)【 ES〕 Ot =● A Snd)― kl lLl● 1+k2“ EJ‐ 〔日 ) dt dP・ k311印 Ell― k4:ElIP〕 at EJ=lEl+〔 ESI Figure l:GeneF● l enZytt knetO equalo器 B ochen■ cal∞ tat,on D D,ffere威 l elualonS COmmontt k.-O h ihe sP∝ おized“ se ofsubsmte mnb面 nL_o The nrsttem m“ e● た面 積 l equalon tor suDま rate cttnge a簑 mes rh/:hm c subslrde inp● inihe rom oia sine wave A subirate input E上 L/ム P k5 sbw fast B k,「 1+k21E l lEi4LSl) dt uES・ k,([印 [同 161)― (k4+kJ 161 1t uS・ lv+A● notl― k,1111-:● }[ESl)S+ヽ lESl dt dP‐ k`[61 dt i[.1‐ [ヽ1【lFSl Foure 2:A)Poss'わ le rea“ on 3cheme for enzyme ca● S ttth subslrate advalon Vang et al t341) B,Set Of direren,al equat rea“ on schett ofttbstrate ad"節 on(E=嘔 .― E ES)The l嵐 lem hthe reacton of substale cha"e assumes th/11m e subst and the宙 sualintlo“ of rate tl・ angts(“ atlVanted enゅ e ttneuぽ . PrOgram in Nellogo Model Llbrary httP′ cd nOrth■ estern edl1/ n.・ tlogO/1110dels′ )nc PrOgram models ule rttral nc tnCuc reac● o“ (■ re l)m■ eaぬ rttctltln constant α l hrougllり i"ほ a stlbttaF volmle,ald the rate orthe lnup mplilldc ad llequen")tO be set by the invc■ gator A srbstrate input i r. E+S ------!- ES k2 EIP J Ploleol cs Bわ nfom iSSN.0● 74-276X」 P3 an open aα 狭奏 `卜 vdure 6(6) r32-!ar (2013) - r33

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Cita● on:Mlmowsk P,Carter TO,Weber OF(2013)Enzyme Cata ysis and he Outcome of 0 0Chem cal Reaい ons U P,oteonics B:o nform 6i 432-

141 doi:10 417211pb 1000271

to allect outcome by turning periodic subslrate inp!t into fl on-periodicprodr.rct generetion has been uncertain. Enamples were found in the(xidase peroxidase reaction J6] and a hemin hydrogen perodde-suirtite model of.atal)$is [7], bul broad potential for non-linearity inother emyme-calallzed systems has not been established. Enzlrnaticreactions.an be described in general tenns by a set of ordinarydifferential equatioDs for aII reactants (Figure 1). Thek format has someresernblance to the differential equations descrihing the t,orellz andRdssler systems ofr}on-lillear dFami.s [8,9], and therelore implies the

?otential to generate cotupiex, possibly chaodc bchavior.

Here we test the h,lothesis that eru,)lnc calallsis can affcct theoutcome of biochemicxl reactions We investigate the panmeterspace for the rate aonstants in substrate-activated and general enzlmecatalysis, and we $tudy enzynre calalysis in a brarched reaction wirltr,o competing arms.

Materials and Methods

L sirico modeling

'Ihe chemical reactioos under study can bc dcfined as sets ofordioary dillerential equations (ODLS) thal describe t})e rate ofchangeof each reactant per time step- TIre soluiions oftllose equations showconstant, peaiodiq ol non-periodic flow over time- Here, a solverftom tr SciPy [t0] package (scipy.intcgrate.odeint) was used to modelen4ane catal)sis. To solve the equations under study, the time step wassct to 0.01 seconds, resulting in a samp[ng frequency of 100 Hz. 'Ihe

inpui fluctuated at a constani rate of0.01 l{2, i.e. each oscil}atioo took100 seconds or 10000 points. A double precision arilhmetic (64 bit)was applied

Non-lir€ar systcrns can be rcpresented in a hifurcation diagramas a set of densely packed poirts- the use of a Fourier transform

Bives another method of visualization. lhe Fourier hansfbrm is

a sigral represe$ation in a liequency space. Wlrereas a siglal int-he time domain shous how much energy is carried in a given timeperiod tLe Fourier spectrum shows how 1i!_h energy is carried in a

given frequency range. 'Ihe periodicity of a siglal is particularly wellrepresented on a Fourier spectrum-a-s a peak at a spediic frequency(and at ha Donic frequencies). Because in the chaos regime everyperiod is presenl, the Irourier spectnfil of a chaotic signal has pealcfor every frequencp

A bilurcation djagram is a graphical method of presefltilrg a

change itl a dyiamical s]Btcm depending on a change in one of theundcrlying parameters. A biiurcation plot represents a map, not a flow(the q itcm is representcd by a recurrencq not difierential, equation). Ifa system has oriy fixed pofurts in sofle parameter rarge, this should be

rcprose[ted on the diagram a5 a solid [ine. Limit cycles are representedas nrultiple, vertical lines. The number of lines depends on the peiiodof oscillations. Chaos in this case is represented as a block of denselypacked points. lo define the reaction states of the enz)'rne catallsis, wegenerxted bjfurcatioB maps by solving the sel of differential equations(Figure 2) fbr each of its parameters At every ite.alion,local minimaand maxima qlues of a chosen variable v.ere plotted on a vertjcal a.xis.

Upon completion of lhe desired range o[ parameters, the resultinggraph pres€nts the change of the system's variables depending on thedelrcd parameter change.

Agent-based modeling

For agent based modeling, a basic Netlrgo model on enzymckineli.s was cdiied to allow for contjnuous rh)4llmic substrate input

BdE=(峰 +k,)(IEtl lFl)一 kl:E]ISI― k41E〕 111

dt

dES・ kl l【 ]lS〕+К4[E]【 P〕 ―(k2+k3)【 ES〕

Ot

坐=● やA Snd)― kl lLl● 1+k2“ EJ‐〔日)

dt

dP・ k311印 〔Ell― k4:ElIP〕

at

〔EJ=lEl+〔 ESI

Figure l:GeneF●l enZytt knetO equalo器 ~

B ochen■cal∞tat,on DD,ffere威●l elualonS COmmontt k.-O h ihe sP∝ おized“se ofsubsmtemnb面。nL_o The nrsttem m“e●た面 積l equalon tor suDま rate cttnge

a簑鶏mes rh/:hm c subslrde inp● inihe rom oia sine wave

Asubirate

input

E上ざ‐鼻 郎ちヽ、、L/ム、Pk5

sbw fast

B I延 ―k,「1+k21E l lEi4LSl)dt

uES・ k,([印 [同161)― (k4+kJ 1611t

uS・ lv+A● notl― k,1111-:● }[ESl)S+ヽ lESl

dt

dP‐ k`[61dt

i[.1‐ [ヽ 1【呵 lFSl

Foure 2:A)Poss'わ le rea“ on 3cheme for enzyme ca● 呼●S ttth subslrate

advalon ″Vang et al t341) B,Set Of direren,al equations desc10ing lherea“on schett ofttbstrate ad"節 on(E=嘔

.―E ES)The l嵐 lem hthe

reacton of substale cha"e assumes th/11m e substrate inplt n the brm ol

and the宙sualintlo“ of rate tl・ angts(“ atlVanted enゅ 唖e ttneuぽ .

PrOgram in Nellogo Model Llbrary httP′ ′cd nOrth■ estern edl1/

n.・tlogO/1110dels′ )nc PrOgram models ule rttral en″ nc tnCuc

reac● o“ (■諄 re l)m■ eaぬ rttctltln constant αl hrougllり i"ほastlbttaF volmle,ald the rate orthe lnupg lor∝ ●mplilldc ad

llequen")tO be set by the invc■ gator

A srbstrate

inputi r.

E+S ------!- ESk2

k3一

k4

EIP

J Ploleol cs Bわ nfomiSSN.0● 74-276X」 P3 an open aα 狭奏

`卜由mЫ

vdure 6(6) r32-!ar (2013) - r33