Thermodynamic modeling of the partitioning of biomolecules in aqueous two-phase systems using a modified Flory–Huggins equation

Filho, Pedro de Alcântara Pessôa; Mohamed, Rahoma S.

doi:10.1016/j.procbio.2003.10.012

Cited by 18 publications

(5 citation statements)

References 24 publications

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“…The minimization procedure was conducted considering different number of pseudocomponents. It was observed that using more than six pseudocomponents did not change equilibrium calculations, in agreement with literature . Therefore, the calculations were carried out considering either a single pseudocomponent (i.e., considering a monodisperse system) or six pseudocomponents.…”

Section: Resultssupporting

confidence: 81%

“…It was observed that using more than six pseudocomponents did not change equilibrium calculations, in agreement with literature. 25 Therefore, the calculations were carried out considering either a single pseudocomponent (i.e., considering a monodisperse system) or six pseudocomponents. When considering polydispersity, the structure parameters for the maltodextrin pseudocomponents were calculated through r i = 0.03982•(M i / g•mol −1 ) and q i = 0.03627•(M i /g•mol −1 ), wherein M i is the molar mass of each pseudocomponent.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

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Liquid–Liquid Equilibrium of Aqueous Biphasic Systems Containing Ethylene Oxide–Propylene Oxide Block Copolymers and Maltodextrins

Filho

Meirelles

2014

J. Chem. Eng. Data

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This work presents liquid−liquid phase equilibrium data of ternary systems formed by aqueous mixtures of ethylene oxide−propylene oxide block copolymers and maltodextrin. Phase diagrams were obtained for five copolymers (with EO ratios ranging from 20 % to 80 % and molar masses ranging from 1900 g•mol −1 to 8400 g•mol −1 ) and three maltodextrins (with number averaged molar masses of 990 g•mol −1 , 1500 g•mol −1 , and 3000 g•mol −1 ) at 298.2 K and 308.2 K. The main factor influencing the phase diagrams is the ratio between ethylene oxide and propylene oxide chain sizes. The size distribution of maltodextrin was studied through gel permeation chromatography, and the size distribution of some equilibrium phases was also determined. Maltodextrin was found to partition unevenly between equilibrium phases, with larger molecules being excluded from the polymer-rich phases. The phase equilibrium was modeled using the UNIQUAC equation and with the consideration that maltodextrin can be represented by six pseudocomponents. It was verified not only that the model can adequately describe the phase equilibrium but also that the uneven distribution of maltodextrin molecules can be qualitatively assessed.

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Section: Resultssupporting

confidence: 81%

Section: ■ Results and Discussionmentioning

confidence: 99%

Liquid–Liquid Equilibrium of Aqueous Biphasic Systems Containing Ethylene Oxide–Propylene Oxide Block Copolymers and Maltodextrins

Filho

Meirelles

2014

J. Chem. Eng. Data

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“…The Flory Huggins lattice model can be used to predict the miscibility of two compounds, where details of the energetic interactions between the two mixed compounds are described using a single quantity, the Flory–Huggins χ parameter. , However, calculating this quantity requires measurements of polymer–polymer, solvent–solvent, and polymer–solvent interaction energies either through inverse gas chromatography, or by estimating these quantities using molecular dynamics simulations . Although Flory–Huggins theory drastically simplifies complicated molecular structure information, the approach is capable of accurately predicting the miscibility of many polymer–polymer mixtures, most famously the widely used poly(ethylene glycol)-dextran system , for which the interaction parameters are well established. However, there are also many compounds for which Flory–Huggins theory is inadequate for accurately predicting miscibility.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Mixing Behavior of Aqueous Solutions Using a Machine Learning Framework

Peacock

Lamont

Sheen

et al. 2021

ACS Appl. Mater. Interfaces

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The most direct approach to determining if two aqueous solutions will phase-separate upon mixing is to exhaustively screen them in a pair-wise fashion. This is a timeconsuming process that involves preparation of numerous stock solutions, precise transfer of highly concentrated and often viscous solutions, exhaustive agitation to ensure thorough mixing, and time-sensitive monitoring to observe the presence of emulsion characteristics indicative of phase separation. Here, we examined the pair-wise mixing behavior of 68 water-soluble compounds by observing the formation of microscopic phase boundaries and droplets of 2278 unique 2-component solutions. A series of machine learning classifiers (artificial neural network, random forest, k-nearest neighbors, and support vector classifier) were then trained on physicochemical property data associated with the 68 compounds and used to predict their miscibility upon mixing. Miscibility predictions were then compared to the experimental observations. The random forest classifier was the most successful classifier of those tested, displaying an average receiver operator characteristic area under the curve of 0.74. The random forest classifier was validated by removing either one or two compounds from the input data, training the classifier on the remaining data and then predicting the miscibility of solutions involving the removed compound(s) using the classifier. The accuracy, specificity, and sensitivity of the random forest classifier were 0.74, 0.80, and 0.51, respectively, when one of the two compounds to be examined was not represented in the training data. When asked to predict the miscibility of two compounds, neither of which were represented in the training data, the accuracy, specificity, and sensitivity values for the random forest classifier were 0.70, 0.82 and 0.29, respectively. Thus, there is potential for this machine learning approach to improve the design of screening experiments to accelerate the discovery of aqueous two-phase systems for numerous scientific and industrial applications.

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“…Perhaps the conceptually simplest and most dramatic improvements in K can be achieved using affinity ligands . Although in the absence of affinity ligands, ATPS optimization can be a process of trial and error, extensive experimental results have appeared, and in some cases, it was possible to isolate the effects of protein size, hydrophobicity, or charge. − In addition, some groups have developed theory for understanding and predicting partitioning in ATPS. ,− For example, Johansson et al have used a modified Flory−Huggins approach to provide a set of simple equations to guide design of ATPS-based separations . More recent modifications of Flory−Huggins theory to account for solvation of the polymers have appeared …”

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confidence: 99%

Nanoparticle Conjugation Increases Protein Partitioning in Aqueous Two-Phase Systems

Long

Keating

2005

Anal. Chem.

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We describe the effect of bioconjugation to colloidal Au nanoparticles on protein partitioning in poly(ethylene glycol) (PEG)/dextran aqueous two-phase systems (ATPS). Horseradish peroxidase (HRP) was conjugated to colloidal Au nanoparticles by direct adsorption. Although HRP alone had very little phase preference, HRP/Au nanoparticle conjugates typically partitioned to the PEG-rich phase, up to a factor of 150:1 for conjugates of 15-nm colloidal Au. Other protein/Au nanoparticle conjugates exhibited partitioning of greater than 2000:1 to the dextran-rich phase, as compared with approximately 5:1 for the free protein. The degree of partitioning was dependent on polymer concentration and molecular weight, nanoparticle diameter, and in some instances, nanoparticle concentration in the ATPS. The substantial improvements in protein partitioning achievable by conjugation to Au nanoparticles appear to result largely from increased surface area of the conjugates and require neither chemical modification of the proteins or polymers with affinity ligands, increased polymer concentrations, nor addition of high concentrations of salts. Adsorption to colloidal particles thus provides an attractive route for increased partitioning of enzymes and other proteins in ATPS. Furthermore, these results point to ATPS partitioning as a powerful means of purification for biomolecule/nanoparticle conjugates, which are increasingly used in diagnostics and materials applications.

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Thermodynamic modeling of the partitioning of biomolecules in aqueous two-phase systems using a modified Flory–Huggins equation

Cited by 18 publications

References 24 publications

Liquid–Liquid Equilibrium of Aqueous Biphasic Systems Containing Ethylene Oxide–Propylene Oxide Block Copolymers and Maltodextrins

Liquid–Liquid Equilibrium of Aqueous Biphasic Systems Containing Ethylene Oxide–Propylene Oxide Block Copolymers and Maltodextrins

Predicting the Mixing Behavior of Aqueous Solutions Using a Machine Learning Framework

Nanoparticle Conjugation Increases Protein Partitioning in Aqueous Two-Phase Systems

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