Patchy Charge Distribution Affects the pH in Protein Solutions during Dialysis

. 2025 Mar 04 ; 41 (8) : 5387-5398. [epub] 20250218

Jazyk angličtina Země Spojené státy americké Médium print-electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid39964136

When using dialysis ultra- or diafiltration to purify protein solutions, a dialysis buffer in the permeate is employed to set the pH in the protein solution. Failure to achieve the target pH may cause undesired precipitation of the valuable product. However, the pH in the permeate differs from that in the retentate, which contains the proteins. Experimental optimization of the process conditions is time-consuming and expensive, while accurate theoretical predictions still pose a major challenge. Current models of dialysis account for the Donnan equilibrium, acid-base properties, and ion-protein interactions, but they neglect the patchy distribution of ionizable groups on the proteins and its impact on the solution properties. Here, we present a simple computational model of a colloidal particle with weakly acidic sites on the surface, organized in patches. This minimalistic model allows systematic variation of the relevant parameters, while simultaneously demonstrating the essential physics governing the acid-base equilibria in protein solutions. Using molecular simulations in the Grand-Reaction ensemble, we demonstrate that interactions between ionizable sites significantly affect the nanoparticle charge and thereby contribute to pH difference between the permeate and retentate. We show that the significance of this contribution increases if the ionizable sites are located on a smaller patch. Protein solutions are governed by the same physics as our simple model. In this context, our results show that models which aim to quantitatively predict the pH in protein solutions during dialysis need to account for the patchy distribution of ionizable sites on the protein surface.

Zobrazit více v PubMed

Liderfelt J.; Royce J.. Biopharmaceutical Processing; Jagschies G.; Lindskog E.; Ła̧cki K.; Galliher P., Eds.; Elsevier, 2018; pp 441–453.

Zydney A. L. New developments in membranes for bioprocessing - A review. J. Membr. Sci. 2021, 620, 11880410.1016/j.memsci.2020.118804. DOI

Stoner M. R.; Fischer N.; Nixon L.; Buckel S.; Benke M.; Austin F.; Randolph T. W.; Kendrick B. S. Protein-solute interactions affect the outcome of ultrafiltration/diafiltration operations. J. Pharm. Sci. 2004, 93, 2332–2342. 10.1002/jps.20145. PubMed DOI

Bolton G. R.; Boesch A. W.; Basha J.; LaCasse D. P.; Kelley B. D.; Acharya H. Effect of protein and solution properties on the donnan effect during the ultrafiltration of proteins. Biotechnol. Prog. 2011, 27, 140–152. 10.1002/btpr.523. PubMed DOI

Briskot T.; Hillebrandt N.; Kluters S.; Wang G.; Studts J.; Hahn T.; Huuk T.; Hubbuch J. Modeling the Gibbs-Donnan effect during ultrafiltration and diafiltration processes using the Poisson-Boltzmann theory in combination with a basic Stern model. J. Membr. Sci. 2022, 648, 12033310.1016/j.memsci.2022.120333. DOI

Miao F.; Velayudhan A.; DiBella E.; Shervin J.; Felo M.; Teeters M.; Alred P. Theoretical analysis of excipient concentrations during the final ultrafiltration/diafiltration step of therapeutic antibody. Biotechnol. Prog. 2009, 25, 964–972. 10.1002/btpr.168. PubMed DOI

Teeters M.; Bezila D.; Benner T.; Alfonso P.; Alred P. Predicting diafiltration solution compositions for final ultrafiltration/diafiltration steps of monoclonal antibodies. Biotechnol. Bioeng. 2011, 108, 1338–1346. 10.1002/bit.23067. PubMed DOI

Baek Y.; Singh N.; Arunkumar A.; Borwankar A.; Zydney A. L. Mass Balance Model with Donnan Equilibrium Accurately Describes Unusual pH and Excipient Profiles during Diafiltration of Monoclonal Antibodies. Biotechnol. J. 2019, 14, 180051710.1002/biot.201800517. PubMed DOI

Jabra M. G.; Tao Y.; Moomaw J. F.; Yu Z.; Hotovec B. J.; Geng S. B.; Zydney A. L. pH and excipient profiles during formulation of highly concentrated biotherapeutics using bufferless media. Biotechnol. Bioeng. 2020, 117, 3390–3399. 10.1002/bit.27502. PubMed DOI

Ambrožič R.; Arzenšek D.; Podgornik A. Designing scalable ultrafiltration/diafiltration process of monoclonal antibodies via mathematical modeling by coupling mass balances and Poisson-Boltzmann equation. Biotechnol. Bioeng. 2021, 118, 633–646. 10.1002/bit.27598. PubMed DOI

Ladwig J. E.; Zhu X.; Rolandi P.; Hart R.; Robinson J.; Rydholm A. Mechanistic model of pH and excipient concentration during ultrafiltration and diafiltration processes of therapeutic antibodies. Biotechnol. Prog. 2020, 36, e299310.1002/btpr.2993. PubMed DOI

Hebbi V.; Roy S.; Rathore A. S.; Shukla A. Modeling and prediction of excipient and pH drifts during ultrafiltration/diafiltration of monoclonal antibody biotherapeutic for high concentration formulations. Sep. Purif. Technol. 2020, 238, 11639210.1016/j.seppur.2019.116392. DOI

Thakur G.; Hebbi V.; Rathore A. S. Near Infrared Spectroscopy as a PAT tool for monitoring and control of protein and excipient concentration in ultrafiltration of highly concentrated antibody formulations. Int. J. Pharm. 2021, 600, 12045610.1016/j.ijpharm.2021.120456. PubMed DOI

Adair G. S. On the Donnan Equilibrium and the Equation of Gibbs. Science 1923, 58, 13.10.1126/science.58.1488.13.a. PubMed DOI

Landsgesell J.; Beyer D.; Hebbeker P.; Košovan P.; Holm C. The pH-Dependent Swelling of Weak Polyelectrolyte Hydrogels Modeled at Different Levels of Resolution. Macromolecules 2022, 55, 3176–3188. 10.1021/acs.macromol.1c02489. DOI

Landsgesell J.; Hebbeker P.; Rud O.; Lunkad R.; Košovan P.; Holm C. Grand-Reaction Method for Simulations of Ionization Equilibria Coupled to Ion Partitioning. Macromolecules 2020, 53, 3007–3020. 10.1021/acs.macromol.0c00260. DOI

Harvey D.Modern Analytical Chemistry; McGraw Hill, 2000.

Nelson D. L.; Lehninger A. L.; Cox M. M.. Lehninger Principles of Biochemistry; Macmillan, 2008.

Po H. N.; Senozan N. M. The Henderson-Hasselbalch Equation: Its History and Limitations. J. Chem. Educ. 2001, 78, 1499.10.1021/ed078p1499. DOI

Petrucci R. H.; Herring F. G.; Madura J. D.; Bissonnette C.. General Chemistry: Principles and Modern Applications, 11th ed.; Pearson, 1997.

Boubeta F. M.; Soler-Illia G. J. A. A.; Tagliazucchi M.; et al. Electrostatically Driven Protein Adsorption: Charge Patches versus Charge Regulation. Langmuir 2018, 34, 15727–15738. 10.1021/acs.langmuir.8b03411. PubMed DOI

Yuan J.; Takae K.; Tanaka H. Impact of Charge Regulation on Self-Assembly of Zwitterionic Nanoparticles. Phys. Rev. Lett. 2022, 128, 15800110.1103/PhysRevLett.128.158001. PubMed DOI

Rathee V. S.; Zervoudakis A. J.; Sidky H.; Sikora B. J.; Whitmer J. K. Weak polyelectrolyte complexation driven by associative charging. J. Chem. Phys. 2018, 148, 11490110.1063/1.5017941. PubMed DOI

Rathee V. S.; Sidky H.; Sikora B. J.; Whitmer J. K. Role of Associative Charging in the Entropy-Energy Balance of Polyelectrolyte Complexes. J. Am. Chem. Soc. 2018, 140, 15319–15328. 10.1021/jacs.8b08649. PubMed DOI

Pineda S. P.; Staňo R.; Murmiliuk A.; Blanco P. M.; Montes P.; Tošner Z.; Groborz O.; Pánek J.; Hrubý M.; Štěpánek M.; Košovan P. Charge Regulation Triggers Condensation of Short Oligopeptides to Polyelectrolytes. JACS Au 2024, 4, 1775–1785. 10.1021/jacsau.3c00668. PubMed DOI PMC

Barroso da Silva F. L.; Lund M.; Jönsson B.; Åkesson T. On the Complexation of Proteins and Polyelectrolytes. J. Phys. Chem. B 2006, 110, 4459–4464. 10.1021/jp054880l. PubMed DOI

Barroso da Silva F. L.; MacKernan D. Benchmarking a Fast Proton Titration Scheme in Implicit Solvent for Biomolecular Simulations. J. Chem. Theory Comput. 2017, 13, 2915–2929. 10.1021/acs.jctc.6b01114. PubMed DOI

Lund M.; Jönsson B. Charge regulation in biomolecular solution. Q. Rev. Biophys. 2013, 46, 265–268. 10.1017/S003358351300005X. PubMed DOI

Ausserwöger H.; Krainer G.; Welsh T. J.; Thorsteinson N.; De Csilléry E.; Sneideris T.; Schneider M. M.; Egebjerg T.; Invernizzi G.; Herling T. W.; Lorenzen N.; Knowles T. P. J. Surface patches induce nonspecific binding and phase separation of antibodies. Proc. Natl. Acad. Sci. U.S.A. 2023, 120, e221033212010.1073/pnas.2210332120. PubMed DOI PMC

Jacobs M. I.; Bansal P.; Shukla D.; Schroeder C. M. Understanding Supramolecular Assembly of Supercharged Proteins. ACS Cent. Sci. 2022, 8, 1350–1361. 10.1021/acscentsci.2c00730. PubMed DOI PMC

Kim J.; Qin S.; Zhou H.-X.; Rosen M. K. Surface Charge Can Modulate Phase Separation of Multidomain Proteins. J. Am. Chem. Soc. 2024, 146, 3383–3395. 10.1021/jacs.3c12789. PubMed DOI PMC

Teixeira A. A. R.; Lund M.; Barroso da Silva F. L. Fast Proton Titration Scheme for Multiscale Modeling of Protein Solutions. J. Chem. Theory Comput. 2010, 6, 3259–3266. 10.1021/ct1003093. PubMed DOI

Lošdorfer Božič A.; Podgornik R. pH Dependence of Charge Multipole Moments in Proteins. Biophys. J. 2017, 113, 1454–1465. 10.1016/j.bpj.2017.08.017. PubMed DOI PMC

Božič A.; Podgornik R. Site Correlations, Capacitance, and Polarizability From Protein Protonation Fluctuations. J. Phys. Chem. B 2021, 125, 12902–12908. 10.1021/acs.jpcb.1c08200. PubMed DOI

Podgornik R. General theory of charge regulation and surface differential capacitance. J. Chem. Phys. 2018, 149, 10470110.1063/1.5045237. PubMed DOI

Avni Y.; Andelman D.; Podgornik R. Charge regulation with fixed and mobile charged macromolecules. Curr. Opin. Electrochem. 2019, 13, 70–77. 10.1016/j.coelec.2018.10.014. DOI

Katchalsky A.; Gillis J. Theory of the potentiometric titration of polymeric acids. Recl. Trav. Chim. Pays-Bas 1949, 68, 879.10.1002/recl.19490680912. DOI

Katchalsky A.; Lifson S.; Mazur J. The electrostatic free energy of polyelectrolyte solutions. I. Randomly kinked macromolecules. J. Polym. Sci. 1953, 11, 409–423. 10.1002/pol.1953.120110503. DOI

Arnold R. The titration of polymeric acids. J. Colloid Sci. 1957, 12, 549–556. 10.1016/0095-8522(57)90060-0. DOI

Mandel M. The potentiometric titration of weak polyacids. Eur. Polym. J. 1970, 6, 807–822. 10.1016/0014-3057(70)90005-4. DOI

Ullner M.; Jönsson B.; Widmark P. Conformational properties and apparent dissociation constants of titrating polyelectrolytes: Monte Carlo simulation and scaling arguments. J. Chem. Phys. 1994, 100, 3365.10.1063/1.466378. DOI

Ullner M.; Jönsson B.; Söderberg B.; Peterson C. A Monte Carlo study of titrating polyelectrolytes. J. Chem. Phys. 1996, 104, 3048–3057. 10.1063/1.471071. DOI

Borkovec M.; Koper G. J. M. A Cluster Expansion Method for the Complete Resolution of Microscopic Ionization Equilibria from NMR Titrations. Anal. Chem. 2000, 72, 3272–3279. 10.1021/ac991494p. PubMed DOI

Avni Y.; Podgornik R.; Andelman D. Critical behavior of charge-regulated macro-ions. J. Chem. Phys. 2020, 153, 02490110.1063/5.0011623. PubMed DOI

Ferrari S.; Bianchi E.; Kahl G. Spontaneous assembly of a hybrid crystal-liquid phase in inverse patchy colloid systems. Nanoscale 2017, 9, 1956–1963. 10.1039/C6NR07987C. PubMed DOI PMC

Bianchi E.; van Oostrum P. D.; Likos C. N.; Kahl G. Inverse patchy colloids: Synthesis, modeling and self-organization. Curr. Opin. Colloid Interface Sci. 2017, 30, 8–15. 10.1016/j.cocis.2017.03.010. DOI

Notarmuzi D.; Bianchi E.. Liquid-liquid phase separation driven by charge heterogeneity. arXiv:2401.10655. arXiv.org e-Print archive. https://arxiv.org/abs/2401.10655, 2024. PubMed PMC

Dempster J. M.; Olvera De La Cruz M. Aggregation of Heterogeneously Charged Colloids. ACS Nano 2016, 10, 5909–5915. 10.1021/acsnano.6b01218. PubMed DOI

Popa I.; Papastavrou G.; Borkovec M. Charge regulation effects on electrostatic patch-charge attraction induced by adsorbed dendrimers. Phys. Chem. Chem. Phys. 2010, 12, 4863.10.1039/b925812d. PubMed DOI

da Silva F. L. B.; Jönsson B. Polyelectrolyte-protein complexation driven by charge regulation. Soft Matter 2009, 5, 2862.10.1039/b902039j. DOI

Blanco P. M.; Achetoni M. M.; Garcés J. L.; Madurga S.; Mas F.; Baieli M. F.; Narambuena C. F. Adsorption of flexible proteins in the ‘wrong side’ of the isoelectric point: casein macropeptide as a model system. Colloids Surf., B 2022, 217, 11261710.1016/j.colsurfb.2022.112617. PubMed DOI

Henzler K.; Haupt B.; Lauterbach K.; Wittemann A.; Borisov O.; Ballauff M. Adsorption of β-actoglobulin on spherical polyelectrolyte brushes: Direct proof of counterion release by isothermal titration calorimetry. J. Am. Chem. Soc. 2010, 132, 3159–3163. 10.1021/ja909938c. PubMed DOI

Yigit C.; Kanduč M.; Ballauff M.; Dzubiella J. Interaction of Charged Patchy Protein Models with Like-Charged Polyelectrolyte Brushes. Langmuir 2017, 33, 417–427. 10.1021/acs.langmuir.6b03797. PubMed DOI

Lunkad R.; Barroso da Silva F. L.; Košovan P. Both Charge-Regulation and Charge-Patch Distribution Can Drive Adsorption on the Wrong Side of the Isoelectric Point. J. Am. Chem. Soc. 2022, 144, 1813–1825. 10.1021/jacs.1c11676. PubMed DOI

Staňo R.; Košovan P.; Tagliabue A.; Holm C. Electrostatically Cross-Linked Reversible Gels–Effects of pH and Ionic Strength. Macromolecules 2021, 54, 4769–4781. 10.1021/acs.macromol.1c00470. DOI

Košovan P.; Richter T.; Holm C. Modelling of polyelectrolyte gels in equilibrium with salt solutions. Macromolecules 2015, 48, 7698–7708. 10.1021/acs.macromol.5b01428. DOI

Hebbeker P.; Blanco P. M.;Uhlík F.; Kosovan P.. Finite-Size Effects in Simulations of Chemical Reactions. 2023; https://chemrxiv.org/engage/chemrxiv/article-details/64da8a8969bfb8925aef5685.

Hockney R. W.; Eastwood J. W.. Computer Simulation Using Particles; Taylor & Francis, New York, 1988.

Deserno M.; Holm C. How to mesh up Ewald sums. I. A theoretical and numerical comparison of various particle mesh routines. J. Chem. Phys. 1998, 109, 7678–7693. 10.1063/1.477414. DOI

Deserno M.; Holm C. How to mesh up Ewald sums. II. An accurate error estimate for the particle–particle–particle-mesh algorithm. J. Chem. Phys. 1998, 109, 7694–7701. 10.1063/1.477415. DOI

Weeber R.; Grad J.-N.; Beyer D.; Blanco P. M.; Kreissl P.; Reinauer A.; Tischler I.; Košovan P.; Holm C.. Reference Module in Chemistry, Molecular Sciences and Chemical Engineering; Elsevier, 2023.

Smith W. R.; Tříska B. The reaction ensemble method for the computer simulation of chemical and phase equilibria. I. Theory and basic examples. J. Chem. Phys. 1994, 100, 3019–3027. 10.1063/1.466443. DOI

Weik F.; Weeber R.; Szuttor K.; Breitsprecher K.; de Graaf J.; Kuron M.; Landsgesell J.; Menke H.; Sean D.; Holm C. ESPResSo 4.0 - an extensible software package for simulating soft matter systems. Eur. Phys. J. Spec. Top. 2019, 227, 1789–1816. 10.1140/epjst/e2019-800186-9. DOI

Janke W.Statistical Analysis of Simulations: Data Correlations and Error Estimation. In Quantum Simulations of Complex Many-Body Systems: Theory To Algorithm 2002; pp 423–445.

Beyer D.; Košovan P.; Holm C. Simulations Explain the Swelling Behavior of Hydrogels with Alternating Neutral and Weakly Acidic Blocks. Macromolecules 2022, 55, 10751–10760. 10.1021/acs.macromol.2c01916. DOI

Wennerström H.; Vallina Estrada E.; Danielsson J.; Oliveberg M. Colloidal stability of the living cell. Proc. Natl. Acad. Sci. U.S.A. 2020, 117, 10113–10121. 10.1073/pnas.1914599117. PubMed DOI PMC

Arkhipov A.; Schulten K.; Freddolino P.; Ying Y.; Shih A.; Chen Z.. Coarse-Graining of Condensed Phase and Biomolecular Systems; Voth G., Ed.; CRC Press, 2008; pp 299–315.

Najít záznam

Citační ukazatele

Pouze přihlášení uživatelé

Možnosti archivace

Nahrávání dat ...