Literature DB >> 20959107

Diffusion and sedimentation interaction parameters for measuring the second virial coefficient and their utility as predictors of protein aggregation.

Atul Saluja1, R Matthew Fesinmeyer, Sabine Hogan, David N Brems, Yatin R Gokarn.   

Abstract

The concentration-dependence of the diffusion and sedimentation coefficients (k(D) and k(s), respectively) of a protein can be used to determine the second virial coefficient (B₂), a parameter valuable in predicting protein-protein interactions. Accurate measurement of B₂ under physiologically and pharmaceutically relevant conditions, however, requires independent measurement of k(D) and k(s) via orthogonal techniques. We demonstrate this by utilizing sedimentation velocity (SV) and dynamic light scattering (DLS) to analyze solutions of hen-egg white lysozyme (HEWL) and a monoclonal antibody (mAb1) in different salt solutions. The accuracy of the SV-DLS method was established by comparing measured and literature B₂ values for HEWL. In contrast to the assumptions necessary for determining k(D) and k(s) via SV alone, k(D) and ks were of comparable magnitudes, and solution conditions were noted for both HEWL and mAb1 under which 1), k(D) and k(s) assumed opposite signs; and 2), k(D) ≥k(s). Further, we demonstrate the utility of k(D) and k(s) as qualitative predictors of protein aggregation through agitation and accelerated stability studies. Aggregation of mAb1 correlated well with B₂, k(D), and k(s), thus establishing the potential for k(D) to serve as a high-throughput predictor of protein aggregation.
Copyright © 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20959107      PMCID: PMC2955502          DOI: 10.1016/j.bpj.2010.08.020

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  44 in total

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2.  Rapid measurement of protein osmotic second virial coefficients by self-interaction chromatography.

Authors:  Peter M Tessier; Abraham M Lenhoff; Stanley I Sandler
Journal:  Biophys J       Date:  2002-03       Impact factor: 4.033

3.  Non-ideality by sedimentation velocity of halophilic malate dehydrogenase in complex solvents.

Authors:  A Solovyova; P Schuck; L Costenaro; C Ebel
Journal:  Biophys J       Date:  2001-10       Impact factor: 4.033

Review 4.  Physical stability of proteins in aqueous solution: mechanism and driving forces in nonnative protein aggregation.

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Journal:  Pharm Res       Date:  2003-09       Impact factor: 4.200

5.  Protein interactions in undersaturated and supersaturated solutions: a study using light and x-ray scattering.

Authors:  Janaky Narayanan; X Y Liu
Journal:  Biophys J       Date:  2003-01       Impact factor: 4.033

6.  Self-interaction chromatography: a novel screening method for rational protein crystallization.

Authors:  Peter M Tessier; Scott D Vandrey; Bryan W Berger; Rajesh Pazhianur; Stanley I Sandler; Abraham M Lenhoff
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7.  The likelihood of aggregation during protein renaturation can be assessed using the second virial coefficient.

Authors:  Jason G S Ho; Anton P J Middelberg; Paul Ramage; Hans P Kocher
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8.  Measurements of protein-protein interactions by size exclusion chromatography.

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Journal:  Biochemistry       Date:  2002-05-21       Impact factor: 3.162

10.  Size-distribution analysis of macromolecules by sedimentation velocity ultracentrifugation and lamm equation modeling.

Authors:  P Schuck
Journal:  Biophys J       Date:  2000-03       Impact factor: 4.033

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  35 in total

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2.  Assessing the Structures and Interactions of γD-Crystallin Deamidation Variants.

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3.  Reexamining protein-protein and protein-solvent interactions from Kirkwood-Buff analysis of light scattering in multi-component solutions.

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Journal:  J Chem Phys       Date:  2011-06-14       Impact factor: 3.488

4.  Rational design of viscosity reducing mutants of a monoclonal antibody: hydrophobic versus electrostatic inter-molecular interactions.

Authors:  Pilarin Nichols; Li Li; Sandeep Kumar; Patrick M Buck; Satish K Singh; Sumit Goswami; Bryan Balthazor; Tami R Conley; David Sek; Martin J Allen
Journal:  MAbs       Date:  2015       Impact factor: 5.857

5.  In vitro and in silico assessment of the developability of a designed monoclonal antibody library.

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Journal:  MAbs       Date:  2019-01-18       Impact factor: 5.857

6.  High Throughput Prediction Approach for Monoclonal Antibody Aggregation at High Concentration.

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Journal:  Pharm Res       Date:  2017-06-07       Impact factor: 4.200

7.  Challenges in Predicting Protein-Protein Interactions from Measurements of Molecular Diffusivity.

Authors:  Lea L Sorret; Madison A DeWinter; Daniel K Schwartz; Theodore W Randolph
Journal:  Biophys J       Date:  2016-11-01       Impact factor: 4.033

8.  AUC measurements of diffusion coefficients of monoclonal antibodies in the presence of human serum proteins.

Authors:  Robert T Wright; David Hayes; Peter J Sherwood; Walter F Stafford; John J Correia
Journal:  Eur Biophys J       Date:  2018-07-12       Impact factor: 1.733

9.  In Silico Prediction of Diffusion Interaction Parameter (kD), a Key Indicator of Antibody Solution Behaviors.

Authors:  Dheeraj S Tomar; Satish K Singh; Li Li; Matthew P Broulidakis; Sandeep Kumar
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10.  Weak interactions govern the viscosity of concentrated antibody solutions: high-throughput analysis using the diffusion interaction parameter.

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