2020
DOI: 10.1021/acs.molpharmaceut.9b00960
|View full text |Cite
|
Sign up to set email alerts
|

Coarse-Grained Molecular Dynamics Simulations for Understanding the Impact of Short-Range Anisotropic Attractions on Structure and Viscosity of Concentrated Monoclonal Antibody Solutions

Abstract: Understanding protein–protein interactions in concentrated therapeutic monoclonal antibody (mAb) solutions is desirable for improved drug discovery, processing, and administration. Here, we deduce both the net protein charge and the magnitude and geometry of short-ranged, anisotropic attractions of a mAb across multiple concentrations and cosolute conditions by comparing structure factors S(q) obtained from small-angle X-ray scattering experiments with those from molecular dynamics (MD) simulations. The simula… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

4
74
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 30 publications
(78 citation statements)
references
References 37 publications
4
74
0
Order By: Relevance
“…The resulting CG model was used for calculating the cluster size distribution of the solution, which in turn was used to reproduce the solution viscosity via an empirical equation. 88 This approach predicted reasonably well the changes in viscosity with respect to protein concentrations for both mAbs in most of the tested formulations, as well as for a polyclonal IgG; 198 however, it failed to capture these changes when protein clustering is driven by strong anisotropic interactions. More recently, Izadi et al .…”
Section: High-concentration Physical Instabilitiesmentioning
confidence: 94%
See 3 more Smart Citations
“…The resulting CG model was used for calculating the cluster size distribution of the solution, which in turn was used to reproduce the solution viscosity via an empirical equation. 88 This approach predicted reasonably well the changes in viscosity with respect to protein concentrations for both mAbs in most of the tested formulations, as well as for a polyclonal IgG; 198 however, it failed to capture these changes when protein clustering is driven by strong anisotropic interactions. More recently, Izadi et al .…”
Section: High-concentration Physical Instabilitiesmentioning
confidence: 94%
“…As a consequence, it is often observed that these models cannot be transferred between different protein systems, or they are even unable to predict the behavior of the same system at different thermodynamic states. 82 , 87 , 88 Finally, most CG models are developed in an implicit-solvent framework, where the behavior of the solvent and any excipient in solution is averaged out and absorbed in the potential energy function for protein–protein interactions. If one were interested in studying the effects of excipients on the stability of protein solutions (e.g., during formulation screening studies), a different set of CG force-fields for each combination of excipients would be required to carry out such in-silico studies.…”
Section: Types Of Protein Modelsmentioning
confidence: 99%
See 2 more Smart Citations
“… 241–246 Although MD simulation-based parameters, such as short-range interactions, van der Waals attractions and electrostatic repulsions are also used to develop models to predict viscosity of antibodies under a wide range of concentration and ionic strength. 247 , 294 A mutagenesis study using MD simulations and experiments showed that replacing surface-exposed aromatic AA residues reduces the viscosity of antibodies. 248 Schwenger et al 249 measured the viscosity as a function of concentration using Ross-Minton model and temperature using the Arrhenius equation and tested it on four mAbs in the range of potential clinical formulation.…”
Section: Capacity To Modularly Learn Antibody Design Parametersmentioning
confidence: 99%