Combining Scattering Experiments and Colloid Theory to Characterize Charge Effects in Concentrated Antibody Solutions

胶体 化学 化学物理 动态光散射 扩散 离子强度 维里系数 粘度 静电学 电泳 电泳光散射 粒子(生态学) 热力学 材料科学 物理 纳米技术 色谱法 物理化学 纳米颗粒 海洋学 地质学 水溶液
作者
Alessandro Gulotta,Marco Polimeni,Samuel Lenton,Charles G. Starr,Anna Stradner,Emanuela Zaccarelli,Peter Schurtenberger
出处
期刊:Molecular Pharmaceutics [American Chemical Society]
卷期号:21 (5): 2250-2271
标识
DOI:10.1021/acs.molpharmaceut.3c01023
摘要

Charges and their contribution to protein–protein interactions are essential for the key structural and dynamic properties of monoclonal antibody (mAb) solutions. In fact, they influence the apparent molecular weight, the static structure factor, the collective diffusion coefficient, or the relative viscosity, and their concentration dependence. Further, charges play an important role in the colloidal stability of mAbs. There exist standard experimental tools to characterize mAb net charges, such as the measurement of the electrophoretic mobility, the second virial coefficient, or the diffusion interaction parameter. However, the resulting values are difficult to directly relate to the actual overall net charge of the antibody and to theoretical predictions based on its known molecular structure. Here, we report the results of a systematic investigation of the solution properties of a charged IgG1 mAb as a function of concentration and ionic strength using a combination of electrophoretic measurements, static and dynamic light scattering, small-angle X-ray scattering, and tracer particle-based microrheology. We analyze and interpret the experimental results using established colloid theory and coarse-grained computer simulations. We discuss the potential and limits of colloidal models for the description of the interaction effects of charged mAbs, in particular pointing out the importance of incorporating shape and charge anisotropy when attempting to predict structural and dynamic solution properties at high concentrations.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
祖乐萱发布了新的文献求助10
2秒前
陈信宏完成签到,获得积分10
3秒前
3秒前
逍遥子完成签到,获得积分10
3秒前
4秒前
ff发布了新的文献求助10
5秒前
浮游应助djbj2022采纳,获得10
5秒前
科研通AI6应助双夏采纳,获得30
7秒前
冬日空虚完成签到,获得积分10
7秒前
8秒前
10秒前
11秒前
大个应助小黄采纳,获得10
11秒前
12秒前
12秒前
jack发布了新的文献求助10
13秒前
爱笑的天空完成签到,获得积分10
13秒前
14秒前
15秒前
量子星尘发布了新的文献求助10
16秒前
16秒前
simdows完成签到,获得积分10
17秒前
科研通AI6应助季文婷采纳,获得10
17秒前
脑洞疼应助jack采纳,获得10
21秒前
123应助儒雅致远采纳,获得10
21秒前
慕青应助儒雅致远采纳,获得10
21秒前
善学以致用应助万事都灵采纳,获得10
22秒前
Wonder罗完成签到,获得积分20
23秒前
小蘑菇应助坦率幻灵采纳,获得10
27秒前
27秒前
28秒前
29秒前
31秒前
msf0073应助JJJ采纳,获得10
33秒前
躺躺躺发布了新的文献求助10
34秒前
36秒前
37秒前
38秒前
39秒前
量子星尘发布了新的文献求助10
40秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
化妆品原料学 1000
Psychology of Self-Regulation 600
1st Edition Sports Rehabilitation and Training Multidisciplinary Perspectives By Richard Moss, Adam Gledhill 600
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5638000
求助须知:如何正确求助?哪些是违规求助? 4744481
关于积分的说明 15000910
捐赠科研通 4796182
什么是DOI,文献DOI怎么找? 2562369
邀请新用户注册赠送积分活动 1521868
关于科研通互助平台的介绍 1481741