A pK determination method for proteins from titration curves using principle component analysis

Shim, Jaesool; Dutta, Prashanta; Ivory, Cornelius F.

doi:10.1002/aic.11528

Cited by 7 publications

(9 citation statements)

References 29 publications

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“…IEF can be modeled by the mass conservation equation for each ionic component along with the charge conservation and electroneutrality equations. The mass conservation equation for each amphoteric molecule such as proteins and ampholytes can be derived from the individual mass conservation equations of corresponding species as :

\frac{\partial}{\partial t} C_{i} - D_{i} \nabla^{2} C_{i} - \nabla \cdot (ω_{i} 〈z_{i}〉 \nabla ϕ C_{i}) = 0

where

C_{i}

D_{i}

, and

ω_{i}

are concentration, diffusivity, and electrophoretic mobility of amphoteric component i ,

(〈〉, z_{i})

is the net electric charge for the component i that is either calculated from the pK values or found from the titration data , and ϕ is the electric potential. In addition to the amphoteric molecules, an IEF system contains other ionic components such as hydrogen (H) and hydroxyl (OH) ions.…”

Section: Methodsmentioning

confidence: 99%

“…where C i , D i , and i are concentration, diffusivity, and electrophoretic mobility of amphoteric component i, z i is the net electric charge for the component i that is either calculated from the pK values [13,14] or found from the titration data [15], and is the electric potential. In addition to the amphoteric molecules, an IEF system contains other ionic components such as hydrogen (H) and hydroxyl (OH) ions.…”

Section: Mathematical Model Of Iefmentioning

confidence: 99%

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Efficient algorithm for simulation of isoelectric focusing

et al. 2013

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IEF simulation is an effective tool to investigate the transport phenomena and separation performance as well as to design IEF microchip. However, multidimensional IEF simulations are computationally intensive as one has to solve a large number of mass conservation equations for ampholytes to simulate a realistic case. In this study, a parallel scheme for a 2D IEF simulation is developed to reduce the computational time. The calculation time for each equation is analyzed to identify which procedure is suitable for parallelization. As expected, simultaneous solution of mass conservation equations of ampholytes is identified as the computational hot spot, and the computational time can be significantly reduced by parallelizing the solution procedure for that. Moreover, to optimize the computing time, electric potential behavior during transient state is investigated. It is found that for a straight channel the transient variation of electric potential along the channel is negligible in a narrow pH range (5∼8) IEF. Thus the charge conservation equation is solved for the first time step only, and the electric potential obtain from that is used for subsequent calculations. IEF simulations are carried out using this algorithm for separation of cardiac troponin I from serum albumin in a pH range of 5-8 using 192 biprotic ampholytes. Significant reduction in simulation time is achieved using the parallel algorithm. We also study the effect of number of ampholytes to form the pH gradient and its effect in the focusing and separation behavior of cardiac troponin I and albumin. Our results show that, at the completion of separation phase, the pH profile is stepwise for lower number of ampholytes, but becomes smooth as the number of ampholytes increases. Numerical results also show that higher protein concentration can be obtained using higher number of ampholytes.

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\frac{\partial}{\partial t} C_{i} - D_{i} \nabla^{2} C_{i} - \nabla \cdot (ω_{i} 〈z_{i}〉 \nabla ϕ C_{i}) = 0

where

C_{i}

D_{i}

, and

ω_{i}

are concentration, diffusivity, and electrophoretic mobility of amphoteric component i ,

(〈〉, z_{i})

Section: Methodsmentioning

confidence: 99%

Section: Mathematical Model Of Iefmentioning

confidence: 99%

Efficient algorithm for simulation of isoelectric focusing

et al. 2013

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“…Finally, Shim et al recently developed a 2-D simulator and applied it to IEF simulations in straight and contractionÀexpansion microchannels of 1 cm length [70,71,179,180]. Most simulations were performed with 25 carrier ampholytes producing a pH 6-9 gradient and two model proteins, which were described by nine hypothetical pK values [71,179] or hen egg-white lysozyme whose pK a value input was determined from a titration curve [180].…”

Section: Fundamentals Of Iefmentioning

confidence: 99%

“…Most simulations were performed with 25 carrier ampholytes producing a pH 6-9 gradient and two model proteins, which were described by nine hypothetical pK values [71,179] or hen egg-white lysozyme whose pK a value input was determined from a titration curve [180]. Similarly, Chou and Yang reported a 1-D reduced model for the description of ampholyte-based IEF in straight and contractionÀexpansion microchannels [138].…”

Section: Fundamentals Of Iefmentioning

confidence: 99%

“…Models that are currently in use in various laboratories are the 1-D simulators GENTRANS of Mosher et al [44,49,[51][52][53][54][129][130][131][132] and SIMUL5 of Hruška et al [48] (available at http://www.natur.cuni.cz/ Gas), which succeeded SIMUL 4.0 [47]. Interesting new models are those of Bercovici et al [69] (available as the Stanford's Public Release Electrophoretic Separation Solver (SPRESSO), http://microfluidics.stanford.edu/spresso), the 2-D model of Shim et al [70,71,135,136] and the models of Yang and his collaborators [68,138]. The purposes of this review are (i) to provide a brief overview of the specifications of these simulators and how a dynamic simulation is performed, (ii) to demonstrate the versatility and benefits of dynamic computer simulation by discussing high-resolution simulation examples for ZE, ITP, IEF and EKC and (iii) to comprehensively list the applications in which dynamic simulations were reported and used for the description of electrophoretic behavior of sample and buffer components.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic computer simulations of electrophoresis: A versatile research and teaching tool

et al. 2010

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Software is available, which simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. These dynamic models are based upon equations derived from the transport concepts such as electromigration, diffusion, electroosmosis and imposed hydrodynamic buffer flow that are applied to user-specified initial distributions of analytes and electrolytes. They are able to predict the evolution of electrolyte systems together with associated properties such as pH and conductivity profiles and are as such the most versatile tool to explore the fundamentals of electrokinetic separations and analyses. In addition to revealing the detailed mechanisms of fundamental phenomena that occur in electrophoretic separations, dynamic simulations are useful for educational purposes. This review includes a list of current high-resolution simulators, information on how a simulation is performed, simulation examples for zone electrophoresis, ITP, IEF and EKC and a comprehensive discussion of the applications and achievements.

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Dynamic computer simulations of electrophoresis: Three decades of active research

et al. 2009

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Dynamic models for electrophoresis are based upon model equations derived from the transport concepts in solution together with user-inputted conditions. They are able to predict theoretically the movement of ions and are as such the most versatile tool to explore the fundamentals of electrokinetic separations. Since its inception three decades ago, the state of dynamic computer simulation software and its use has progressed significantly and Electrophoresis played a pivotal role in that endeavor as a large proportion of the fundamental and application papers were published in this periodical. Software is available that simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. This has been employed to show the detailed mechanisms of many of the fundamental phenomena that occur in electrophoretic separations. Dynamic electrophoretic simulations are relevant for separations on any scale and instrumental format, including free-fluid preparative, gel, capillary and chip electrophoresis. This review includes a historical overview, a survey of current simulators, simulation examples and a discussion of the applications and achievements of dynamic simulation.

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A pK determination method for proteins from titration curves using principle component analysis

Cited by 7 publications

References 29 publications

Efficient algorithm for simulation of isoelectric focusing

Efficient algorithm for simulation of isoelectric focusing

Dynamic computer simulations of electrophoresis: A versatile research and teaching tool

Dynamic computer simulations of electrophoresis: Three decades of active research

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