亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Binding of excipients is a poor predictor for aggregation kinetics of biopharmaceutical proteins

蛋白质聚集 色谱法 动力学 溶解度 药品 溶解 生物利用度 药物输送
作者
Matja Zalar,Hristo L. Svilenov,Alexander P. Golovanov
出处
期刊:European Journal of Pharmaceutics and Biopharmaceutics [Elsevier]
卷期号:151: 127-136 被引量:5
标识
DOI:10.1016/j.ejpb.2020.04.002
摘要

One of the major challenges in formulation development of biopharmaceuticals is improving long-term storage stability, which is often achieved by addition of excipients to the final formulation. Finding the optimal excipient for a given protein is usually done using a trial-and-error approach, due to the lack of general understanding of how excipients work for a particular protein. Previously, preferential interactions (binding or exclusion) of excipients with proteins were postulated as a mechanism explaining diversity in the stabilisation effects. Weak preferential binding is however difficult to quantify experimentally, and the question remains whether the formulation process should seek excipients which preferentially bind with proteins, or not. Here, we apply solution NMR spectroscopy to comprehensively evaluate protein-excipient interactions between therapeutically relevant proteins and commonly used excipients. Additionally, we evaluate the effect of excipients on thermal and colloidal protein stability, on aggregation kinetics and protein storage stability at elevated temperatures. We show that there is a weak negative correlation between the strength of protein-excipient interactions and effect on enhancing protein thermal stability. We found that the overall protein-excipient binding per se can be a poor criterion for choosing excipients enhancing formulation stability. Experiments on a diverse set of excipients and test proteins reveal that while excipients affect all of the different aspects of protein stability, the effects are very much protein specific, and care must be taken to avoid apparent generalisations if a smaller dataset is being used.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
2秒前
2秒前
星辰大海应助落后从阳采纳,获得10
5秒前
向7看齐发布了新的文献求助10
6秒前
老实的若山完成签到,获得积分10
15秒前
阿泽完成签到 ,获得积分10
16秒前
玩命的鱼完成签到,获得积分10
21秒前
可靠的自行车完成签到,获得积分10
21秒前
帅气绮露完成签到,获得积分20
23秒前
jason完成签到 ,获得积分10
24秒前
27秒前
落后从阳发布了新的文献求助10
30秒前
32秒前
博ge完成签到 ,获得积分10
35秒前
快乐咸鱼完成签到 ,获得积分10
38秒前
小哈完成签到 ,获得积分10
40秒前
科目三应助科研通管家采纳,获得10
41秒前
orixero应助科研通管家采纳,获得10
41秒前
科研通AI2S应助科研通管家采纳,获得10
41秒前
42秒前
bensonyang1013完成签到 ,获得积分10
43秒前
47秒前
47秒前
kk完成签到,获得积分10
48秒前
55秒前
HBXAurora发布了新的文献求助10
1分钟前
哈哈哈完成签到 ,获得积分10
1分钟前
共享精神应助yamo采纳,获得10
1分钟前
1分钟前
1分钟前
大模型应助Quinta采纳,获得10
1分钟前
研友_38KgB8发布了新的文献求助10
1分钟前
1分钟前
1分钟前
身法马可波罗完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
褚明雪完成签到 ,获得积分10
1分钟前
JY应助xxin采纳,获得10
1分钟前
Quinta发布了新的文献求助10
1分钟前
高分求助中
Sustainability in Tides Chemistry 2800
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
Rechtsphilosophie 1000
Bayesian Models of Cognition:Reverse Engineering the Mind 888
Le dégorgement réflexe des Acridiens 800
Defense against predation 800
XAFS for Everyone (2nd Edition) 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3133887
求助须知:如何正确求助?哪些是违规求助? 2784804
关于积分的说明 7768537
捐赠科研通 2440159
什么是DOI,文献DOI怎么找? 1297188
科研通“疑难数据库(出版商)”最低求助积分说明 624901
版权声明 600791