1
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Palakollu V, Motabar L, Roberts CJ. Impact of Glycosylation on Protein-Protein Self-Interactions of Monoclonal Antibodies. Mol Pharm 2024; 21:1414-1423. [PMID: 38386020 DOI: 10.1021/acs.molpharmaceut.3c01069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Protein self-interactions measured via second osmotic virial coefficients (B22) and dynamic light scattering interaction parameter values (kD) are often used as metrics for assessing the favorability of protein candidates and different formulations during monoclonal antibody (MAb) product development. Model predictions of B22 or kD typically do not account for glycans, though glycosylation can potentially impact experimental MAb self-interactions. To the best of our knowledge, the impact of MAb glycosylation on the experimentally measured B22 and kD values has not yet been reported. B22 and kD values of two fully deglycosylated MAbs and their native (i.e., fully glycosylated) counterparts were measured by light scattering over a range of pH and ionic strength conditions. Significant differences between B22 and kD of the native and deglycosylated forms were observed at a range of low to high ionic strengths used to modulate the effect of electrostatic contributions. Differences were most pronounced at low ionic strength, indicating that electrostatic interactions are a contributing factor. Though B22 and kD values were statistically equivalent at high ionic strengths where electrostatics were fully screened, we observed protein-dependent qualitative differences, which indicate that steric interactions may also play a role in the observed B22 and kD differences. A domain-level coarse-grained molecular model accounting for charge differences was considered to potentially provide additional insight but was not fully predictive of the behavior across all of the solution conditions investigated. This highlights that both the level of modeling and lack of inclusion of glycans may limit existing models in making quantitatively accurate predictions of self-interactions.
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Affiliation(s)
- Veerabhadraiah Palakollu
- Department of Chemical & Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States
| | - Lily Motabar
- Department of Chemical & Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States
| | - Christopher J Roberts
- Department of Chemical & Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States
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2
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Forder JK, Palakollu V, Adhikari S, Blanco MA, Derebe MG, Ferguson HM, Luthra SA, Munsell EV, Roberts CJ. Electrostatically Mediated Attractive Self-Interactions and Reversible Self-Association of Fc-Fusion Proteins. Mol Pharm 2024; 21:1321-1333. [PMID: 38334418 DOI: 10.1021/acs.molpharmaceut.3c01009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Attractive self-interactions and reversible self-association are implicated in many problematic solution behaviors for therapeutic proteins, such as irreversible aggregation, elevated viscosity, phase separation, and opalescence. Protein self-interactions and reversible oligomerization of two Fc-fusion proteins (monovalent and bivalent) and the corresponding fusion partner protein were characterized experimentally with static and dynamic light scattering as a function of pH (5 and 6.5) and ionic strength (10 mM to at least 300 mM). The fusion partner protein and monovalent Fc-fusion each displayed net attractive electrostatic self-interactions at pH 6.5 and net repulsive electrostatic self-interactions at pH 5. Solutions of the bivalent Fc-fusion contained higher molecular weight species that prevented quantification of typical interaction parameters (B22 and kD). All three of the proteins displayed reversible self-association at pH 6.5, where oligomers dissociated with increased ionic strength. Coarse-grained molecular simulations were used to model the self-interactions measured experimentally, assess net self-interactions for the bivalent Fc-fusion, and probe the specific electrostatic interactions between charged amino acids that were involved in attractive electrostatic self-interactions. Mayer-weighted pairwise electrostatic energies from the simulations suggested that attractive electrostatic self-interactions at pH 6.5 for the two Fc-fusion proteins were due to cross-domain interactions between the fusion partner domain(s) and the Fc domain.
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Affiliation(s)
- James K Forder
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19713, United States
| | - Veerabhadraiah Palakollu
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19713, United States
| | - Sudeep Adhikari
- Analytical R&D, Digital & NMR Sciences, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Marco A Blanco
- Discovery Pharmaceutical Sciences, Merck & Co., Inc., West Point, Pennsylvania 19486, United States
| | - Mehabaw Getahun Derebe
- Discovery Biologics, Protein Sciences, Merck & Co., Inc., South San Francisco, California 94080, United States
| | - Heidi M Ferguson
- Discovery Pharmaceutical Sciences, Merck & Co., Inc., West Point, Pennsylvania 19486, United States
| | - Suman A Luthra
- Discovery Pharmaceutical Sciences, Merck & Co., Inc., Boston, Massachusetts 02115, United States
| | - Erik V Munsell
- Discovery Pharmaceutical Sciences, Merck & Co., Inc., Boston, Massachusetts 02115, United States
| | - Christopher J Roberts
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19713, United States
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3
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Janke JJ, Starr CG, Kingsbury JS, Furtmann N, Roberts CJ, Calero-Rubio C. Computational Screening for mAb Colloidal Stability with Coarse-Grained, Molecular-Scale Simulations. J Phys Chem B 2024; 128:1515-1526. [PMID: 38315822 DOI: 10.1021/acs.jpcb.3c05303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Monoclonal antibodies (mAbs) are an important modality of protein therapeutics with broad applications for numerous diseases. However, colloidal instabilities occurring at high protein concentrations can limit the ability to develop stable, high-concentration liquid dosage forms that are required for patient-centric, device-mediated products. Therefore, it is advantageous to identify colloidally stable mAbs early in the discovery process to ensure that they are selected for development. Experimental screening for colloidal stability can be time- and resource-consuming and is most feasible at the later stages of drug development due to material requirements. Alternatively, computational approaches have emerging potential to provide efficient screening and focus developmental efforts on mAbs with the greatest developability potential, while providing mechanistic relationships for colloidal instability. In this work, coarse-grained, molecular-scale models were fine-tuned to screen for colloidal stability at amino-acid resolution. This model parameterization provides a framework to screen for mAb self-interactions and extrapolate to bulk solution behavior. This approach was applied to a wide array of mAbs under multiple buffer conditions, demonstrating the utility of the presented computational approach to augment early candidate screening and later formulation strategies for protein therapeutics.
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Affiliation(s)
- J Joel Janke
- Biologics Drug Product Development and Manufacturing, Sanofi, Framingham, Massachusetts 01701, United States
| | - Charles G Starr
- Biologics Drug Product Development and Manufacturing, Sanofi, Framingham, Massachusetts 01701, United States
| | - Jonathan S Kingsbury
- Biologics Drug Product Development and Manufacturing, Sanofi, Framingham, Massachusetts 01701, United States
| | - Norbert Furtmann
- Large Molecules Research Platform, Sanofi-Aventis Deutschland GmbH, Frankfurt 65926, Germany
| | - Christopher J Roberts
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States
| | - Cesar Calero-Rubio
- Biologics Drug Product Development and Manufacturing, Sanofi, Framingham, Massachusetts 01701, United States
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4
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Lou H, Zhang Y, Kuczera K, Hageman MJ, Schöneich C. Molecular Dynamics Simulation of an Iron(III) Binding Site on the Fc Domain of IgG1 Relevant for Visible Light-Induced Protein Fragmentation. Mol Pharm 2024; 21:501-512. [PMID: 38128475 DOI: 10.1021/acs.molpharmaceut.3c00612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Molecular dynamics simulations were employed to investigate the interaction between Fe(III) and an iron-binding site composed of THR259, ASP252, and GLU261 on the Fc domain of an IgG1. The goal was to provide microscopic mechanistic information for the photochemical, iron-dependent site-specific oxidative fragmentation of IgG1 at THR259 reported in our previous paper. The distance between Fe(III) and residues of interest as well as the binding pocket size was examined for both protonated and deprotonated THR259. The Fe(III) binding free energy (ΔG) was estimated by using an umbrella sampling approach. The pKa shift of the THR259 hydroxyl group caused by the presence of nearby Fe(III) was estimated based on a thermodynamic cycle. The simulation results show that Fe(III) resides inside the proposed binding pocket and profoundly changes the pocket configuration. The ΔG values indicate that the pocket possesses a strong binding affinity for Fe(III). Furthermore, Fe(III) profoundly lowers the pKa value of the THR259 hydroxyl group by 5.4 pKa units.
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Affiliation(s)
- Hao Lou
- Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
- Biopharmaceutical Innovation and Optimization Center, University of Kansas, Lawrence, Kansas 66047, United States
| | - Yilue Zhang
- Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
| | - Krzysztof Kuczera
- Department of Chemistry, University of Kansas, Lawrence, Kansas 66045, United States
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66045, United States
| | - Michael J Hageman
- Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
- Biopharmaceutical Innovation and Optimization Center, University of Kansas, Lawrence, Kansas 66047, United States
| | - Christian Schöneich
- Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
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5
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Brudar S, Breydo L, Chung E, Dill KA, Ehterami N, Phadnis K, Senapati S, Shameem M, Tang X, Tayyab M, Hribar-Lee B. Antibody association in solution: cluster distributions and mechanisms. MAbs 2024; 16:2339582. [PMID: 38666507 PMCID: PMC11057677 DOI: 10.1080/19420862.2024.2339582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/02/2024] [Indexed: 05/01/2024] Open
Abstract
Understanding factors that affect the clustering and association of antibodies molecules in solution is critical to their development as therapeutics. For 19 different monoclonal antibody (mAb) solutions, we measured the viscosities, the second virial coefficients, the Kirkwood-Buff integrals, and the cluster distributions of the antibody molecules as functions of protein concentration. Solutions were modeled using the statistical-physics Wertheim liquid-solution theory, representing antibodies as Y-shaped molecular structures of seven beads each. We found that high-viscosity solutions result from more antibody molecules per cluster. Multi-body properties such as viscosity are well predicted experimentally by the 2-body Kirkwood-Buff quantity, G22, but not by the second virial coefficient, B22, and well-predicted theoretically from the Wertheim protein-protein sticking energy. Weakly interacting antibodies are rate-limited by nucleation; strongly interacting ones by propagation. This approach gives a way to relate micro to macro properties of solutions of associating proteins.
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Affiliation(s)
- Sandi Brudar
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, Ljubljana, Slovenia
| | - Leonid Breydo
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Elisha Chung
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Ken A. Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
- Department of Chemistry and Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY, USA
| | - Nasim Ehterami
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Ketan Phadnis
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Samir Senapati
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Mohammed Shameem
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Xiaolin Tang
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Muhammmad Tayyab
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Barbara Hribar-Lee
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, Ljubljana, Slovenia
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6
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Vlachy V, Kalyuzhnyi YV, Hribar-Lee B, Dill KA. Protein Association in Solution: Statistical Mechanical Modeling. Biomolecules 2023; 13:1703. [PMID: 38136574 PMCID: PMC10742237 DOI: 10.3390/biom13121703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/16/2023] [Accepted: 11/20/2023] [Indexed: 12/24/2023] Open
Abstract
Protein molecules associate in solution, often in clusters beyond pairwise, leading to liquid phase separations and high viscosities. It is often impractical to study these multi-protein systems by atomistic computer simulations, particularly in multi-component solvents. Instead, their forces and states can be studied by liquid state statistical mechanics. However, past such approaches, such as the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, were limited to modeling proteins as spheres, and contained no microscopic structure-property relations. Recently, this limitation has been partly overcome by bringing the powerful Wertheim theory of associating molecules to bear on protein association equilibria. Here, we review these developments.
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Affiliation(s)
- Vojko Vlachy
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, 1000 Ljubljana, Slovenia;
| | | | - Barbara Hribar-Lee
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, 1000 Ljubljana, Slovenia;
| | - Ken A. Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, New York, NY 11794, USA;
- Department of Chemistry, Physics and Astronomy, Stony Brook University, New York, NY 11790, USA
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7
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Chowdhury AA, Manohar N, Witek MA, Woldeyes MA, Majumdar R, Qian KK, Kimball WD, Xu S, Lanzaro A, Truskett TM, Johnston KP. Subclass Effects on Self-Association and Viscosity of Monoclonal Antibodies at High Concentrations. Mol Pharm 2023. [PMID: 37191356 DOI: 10.1021/acs.molpharmaceut.3c00023] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
The effects of a subclass of monoclonal antibodies (mAbs) on protein-protein interactions, formation of reversible oligomers (clusters), and viscosity (η) are not well understood at high concentrations. Herein, we quantify a short-range anisotropic attraction between the complementarity-determining region (CDR) and CH3 domains (KCDR-CH3) for vedolizumab IgG1, IgG2, or IgG4 subclasses by fitting small-angle X-ray scattering (SAXS) structure factor Seff(q) data with an extensive library of 12-bead coarse-grained (CG) molecular dynamics simulations. The KCDR-CH3 bead attraction strength was isolated from the strength of long-range electrostatic repulsion for the full mAb, which was determined from the theoretical net charge and a scaling parameter ψ to account for solvent accessibility and ion pairing. At low ionic strength (IS), the strongest short-range attraction (KCDR-CH3) and consequently the largest clusters and highest η were observed with IgG1, the subclass with the most positively charged CH3 domain. Furthermore, the trend in KCDR-CH3 with the subclass followed the electrostatic interaction energy between the CDR and CH3 regions calculated with the BioLuminate software using the 3D mAb structure and molecular interaction potentials. Whereas the equilibrium cluster size distributions and fractal dimensions were determined from fits of SAXS with the MD simulations, the degree of cluster rigidity under flow was estimated from the experimental η with a phenomenological model. For the systems with the largest clusters, especially IgG1, the inefficient packing of mAbs in the clusters played the largest role in increasing η, whereas for other systems, the relative contribution from stress produced by the clusters was more significant. The ability to relate η to short-range attraction from SAXS measurements at high concentrations and to theoretical characterization of electrostatic patches on the 3D surface is not only of fundamental interest but also of practical value for mAb discovery, processing, formulation, and subcutaneous delivery.
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Affiliation(s)
- Amjad A Chowdhury
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Neha Manohar
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Marta A Witek
- Eli Lilly and Company, Indianapolis, Indiana 46225, United States
| | | | - Ranajoy Majumdar
- Eli Lilly and Company, Indianapolis, Indiana 46225, United States
| | - Ken K Qian
- Eli Lilly and Company, Indianapolis, Indiana 46225, United States
| | - William D Kimball
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Shifeng Xu
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Alfredo Lanzaro
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Thomas M Truskett
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Department of Physics, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Keith P Johnston
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
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8
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Hirschmann F, Lopez H, Roosen-Runge F, Seydel T, Schreiber F, Oettel M. Effects of flexibility in coarse-grained models for bovine serum albumin and immunoglobulin G. J Chem Phys 2023; 158:084112. [PMID: 36859072 DOI: 10.1063/5.0132493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023] Open
Abstract
We construct a coarse-grained, structure-based, low-resolution, 6-bead flexible model of bovine serum albumin (BSA, PDB: 4F5S), which is a popular example of a globular protein in biophysical research. The model is obtained via direct Boltzmann inversion using all-atom simulations of a single molecule, and its particular form is selected from a large pool of 6-bead coarse-grained models using two suitable metrics that quantify the agreement in the distribution of collective coordinates between all-atom and coarse-grained Brownian dynamics simulations of solutions in the dilute limit. For immunoglobulin G (IgG), a similar structure-based 12-bead model has been introduced in the literature [Chaudhri et al., J. Phys. Chem. B 116, 8045 (2012)] and is employed here to compare findings for the compact BSA molecule and the more anisotropic IgG molecule. We define several modified coarse-grained models of BSA and IgG, which differ in their internal constraints and thus account for a variation of flexibility. We study denser solutions of the coarse-grained models with purely repulsive molecules (achievable by suitable salt conditions) and address the effect of packing and flexibility on dynamic and static behavior. Translational and rotational self-diffusivity is enhanced for more elastic models. Finally, we discuss a number of effective sphere sizes for the BSA molecule, which can be defined from its static and dynamic properties. Here, it is found that the effective sphere diameters lie between 4.9 and 6.1 nm, corresponding to a relative spread of about ±10% around a mean of 5.5 nm.
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Affiliation(s)
- Frank Hirschmann
- Institute for Applied Physics, University of Tübingen, Auf der Morgenstelle 10, 72076 Tübingen, Germany
| | - Hender Lopez
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Grangegorman D07 ADY7, Ireland
| | - Felix Roosen-Runge
- Department of Biomedical Sciences and Biofilms-Research Center for Biointerfaces (BRCB), Malmö University, 20506 Malmö, Sweden
| | - Tilo Seydel
- Institut Max von Laue-Paul Langevin, 71 Avenue des Martyrs, 38042 Grenoble, France
| | - Frank Schreiber
- Institute for Applied Physics, University of Tübingen, Auf der Morgenstelle 10, 72076 Tübingen, Germany
| | - Martin Oettel
- Institute for Applied Physics, University of Tübingen, Auf der Morgenstelle 10, 72076 Tübingen, Germany
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9
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Chowdhury A, Manohar N, Guruprasad G, Chen AT, Lanzaro A, Blanco M, Johnston KP, Truskett TM. Characterizing Experimental Monoclonal Antibody Interactions and Clustering Using a Coarse-Grained Simulation Library and a Viscosity Model. J Phys Chem B 2023; 127:1120-1137. [PMID: 36716270 DOI: 10.1021/acs.jpcb.2c07616] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Attractive protein-protein interactions in concentrated monoclonal antibody (mAb) solutions may lead to the formation of clusters that increase viscosity. Here, we propose an analytical model that relates mAb solution viscosity to clustering by accounting for the contributions of suboptimal mAb packing within a cluster and cluster fractal dimension. The influence of short-range, anisotropic attractions and long-range Coulombic repulsion on cluster properties is investigated by analyzing the cluster-size distributions, cluster fractal dimensions, radial distribution functions, and static structure factors from a library of coarse-grained molecular dynamics simulations. The library spans a vast range of mAb charges and attractive interactions in solutions of varying ionic strength. We present a framework for combining the viscosity model and simulation library to successfully characterize the attraction, repulsion, and clustering of an experimental mAb in three different pH and cosolute conditions by fitting the measured viscosity or structure factor from small-angle X-ray scattering. At low ionic strength, the cluster-size distribution is impacted by strong charges, and both the viscosity and net charge or structure factor and net charge must be considered to deconvolute the effects of short-range attraction and long-range repulsion.
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Affiliation(s)
- Amjad Chowdhury
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Neha Manohar
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Geetika Guruprasad
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Amy T Chen
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Alfredo Lanzaro
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Marco Blanco
- Analytical Enabling Capabilities, Analytical R&D, Merck & Co., Inc., Rahway, New Jersey07065, United States
| | - Keith P Johnston
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Thomas M Truskett
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States.,Department of Physics, The University of Texas at Austin, Austin, Texas78712, United States
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10
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Abstract
The aggregation propensity of monoclonal antibodies can be modified by adding different cosolutes into the solution. A simple coarse-grained model in the combination with the thermodynamic perturbation theory was used to predict cluster distribution and viscosity of the solutions of IgG4 monoclonal anibody in the presence of L-Arginine Hydrochloride. The data were analysed using binding polynomial to describe the binding of cosolute (Arginine) to the antibody molecule. The results show that by binding to the antibody molecule the cosolute occupies some of the binding sites of the antibody, and in this way reduces the amount of binding sites available to other antibody molecules. The aggregation propensity of the antibody molecules is therefore reduced.
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11
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Shahfar H, O'Brien CJ, Budyak IL, Roberts CJ. Predicting Experimental B22 Values and the Effects of Histidine Charge States for Monoclonal Antibodies Using Coarse-Grained Molecular Simulations. Mol Pharm 2022; 19:3820-3830. [PMID: 36194430 DOI: 10.1021/acs.molpharmaceut.2c00337] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Static light scattering (SLS) was used to characterize five monoclonal antibodies (MAbs) as a function of total ionic strength (TIS) at pH values between 5.5 and 7.0. Second osmotic virial coefficient (B22) values were determined experimentally for each MAb as a function of TIS using low protein concentration SLS data. Coarse-grained molecular simulations were performed to predict the B22 values for each MAb at a given pH and TIS. To include the effect of charge fluctuations of titratable residues in the B22 calculations, a statistical approach was introduced in the Monte Carlo algorithm based on the protonation probability based on a given pH value and the Henderson-Hasselbalch equation. The charged residues were allowed to fluctuate individually, based on the sampled microstates and the influence of electrostatic interactions on net protein-protein interactions during the simulations. Compared to static charge simulations, the new approach provided improved results compared to experimental B22 values at pH conditions near the pKa of titratable residues.
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Affiliation(s)
- Hassan Shahfar
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware19716, United States
| | - Christopher J O'Brien
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware19716, United States
| | - Ivan L Budyak
- Bioproduct Research and Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana46285, United States
| | - Christopher J Roberts
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware19716, United States
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12
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Blanco MA. Computational models for studying physical instabilities in high concentration biotherapeutic formulations. MAbs 2022; 14:2044744. [PMID: 35282775 PMCID: PMC8928847 DOI: 10.1080/19420862.2022.2044744] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.
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Affiliation(s)
- Marco A. Blanco
- Materials and Biophysical Characterization, Analytical R & D, Merck & Co., Inc, Kenilworth, NJ USA
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13
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Shahfar H, Du Q, Parupudi A, Shan L, Esfandiary R, Roberts CJ. Electrostatically Driven Protein-Protein Interactions: Quantitative Prediction of Second Osmotic Virial Coefficients to Aid Antibody Design. J Phys Chem Lett 2022; 13:1366-1372. [PMID: 35112863 DOI: 10.1021/acs.jpclett.1c03669] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Electrostatically driven attractions between proteins can result in issues for therapeutic protein formulations such as solubility limits, aggregation, and high solution viscosity. Previous work showed that a model monoclonal antibody displayed large and potentially problematic electrostatically driven attractions at typical pH (5-8) and ionic strength conditions (∼10-100 mM). Molecular simulations of a hybrid coarse-grained model (1bC/D, one bead per charged site and per domain) were used to predict potential point mutations to identify key charge changes (charge-to-neutral or charge-swap) that could greatly reduce the net attractive protein-protein self-interactions. A series of variants were tested experimentally with static and dynamic light scattering to quantify interactions and compared to model predictions at low and intermediate ionic strength. Differential scanning calorimetry and circular dichroism confirmed minimal impact on structural or thermal stability of the variants. The model provided quantitative/semiquantitative predictions of protein self-interactions compared to experimental results as well as showed which amino acid pairings or groups had the most impact.
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Affiliation(s)
- Hassan Shahfar
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States
- Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, United States
| | - Qun Du
- Department of Antibody Discovery & Protein Engineering, AstraZeneca, 1 MedImmune Way, Gaithersburg, Maryland 20878, United States
| | - Arun Parupudi
- Department of Antibody Discovery & Protein Engineering, AstraZeneca, 1 MedImmune Way, Gaithersburg, Maryland 20878, United States
| | - Lu Shan
- Department of Antibody Discovery & Protein Engineering, AstraZeneca, 1 MedImmune Way, Gaithersburg, Maryland 20878, United States
| | - Reza Esfandiary
- Department of Dosage Form and Design Development, AstraZeneca, 1 MedImmune Way, Gaithersburg, Maryland 20878, United States
| | - Christopher J Roberts
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States
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Mahapatra S, Polimeni M, Gentiluomo L, Roessner D, Frieß W, Peters GHJ, Streicher WW, Lund M, Harris P. Self-Interactions of Two Monoclonal Antibodies: Small-Angle X-ray Scattering, Light Scattering, and Coarse-Grained Modeling. Mol Pharm 2021; 19:508-519. [PMID: 34939811 DOI: 10.1021/acs.molpharmaceut.1c00627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Using light scattering (LS), small-angle X-ray scattering (SAXS), and coarse-grained Monte Carlo (MC) simulations, we studied the self-interactions of two monoclonal antibodies (mAbs), PPI03 and PPI13. With LS measurements, we obtained the osmotic second virial coefficient, B22, and the molecular weight, Mw, of the two mAbs, while with SAXS measurements, we studied the mAbs' self-interaction behavior in the high protein concentration regime up to 125 g/L. Through SAXS-derived coarse-grained representations of the mAbs, we performed MC simulations with either a one-protein or a two-protein model to predict B22. By comparing simulation and experimental results, we validated our models and obtained insights into the mAbs' self-interaction properties, highlighting the role of both ion binding and charged patches on the mAb surfaces. Our models provide useful information about mAbs' self-interaction properties and can assist the screening of conditions driving to colloidal stability.
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Affiliation(s)
- Sujata Mahapatra
- Novozymes A/S, Biologiens Vej 2, 2800 Kgs. Lyngby, Denmark.,Department of Chemistry, Technical University of Denmark, Kemitorvet Building 207, 2800 Kgs. Lyngby, Denmark
| | - Marco Polimeni
- Division of Theoretical Chemistry, Department of Chemistry, Lund University, Naturvetarvägen 14, 223 62 Lund, Sweden
| | - Lorenzo Gentiluomo
- Wyatt Technology Europe GmbH, Hochstrasse 12a, 56307 Dernbach, Germany.,Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig Maximilians-Universität München, Butenandtstrasse 5, 81377 Munich, Germany
| | - Dierk Roessner
- Wyatt Technology Europe GmbH, Hochstrasse 12a, 56307 Dernbach, Germany
| | - Wolfgang Frieß
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig Maximilians-Universität München, Butenandtstrasse 5, 81377 Munich, Germany
| | - Günther H J Peters
- Department of Chemistry, Technical University of Denmark, Kemitorvet Building 207, 2800 Kgs. Lyngby, Denmark
| | | | - Mikael Lund
- Division of Theoretical Chemistry, Department of Chemistry, Lund University, Naturvetarvägen 14, 223 62 Lund, Sweden.,Advanced X-ray and Neutron Science (LINXS), Lund University, Scheelevägen 19, 22370 Lund, Sweden
| | - Pernille Harris
- Department of Chemistry, Technical University of Denmark, Kemitorvet Building 207, 2800 Kgs. Lyngby, Denmark
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