Chemometrics in Protein Formulation: Stability Governed by Repulsion and Protein Unfolding

化学计量学 理论(学习稳定性) 离子强度 蛋白质稳定性 生物系统 偏最小二乘回归 化学 计算机科学 色谱法 机器学习 生物化学 生物 物理化学 水溶液
作者
Alina Kulakova,Dillen Augustijn,Inas El Bialy,Lorenzo Gentiluomo,Maria Laura Greco,Stefan Hervø-Hansen,Sowmya Indrakumar,Sujata Mahapatra,Marcello Martinez Morales,Christin Pohl,Marco Polimeni,Aisling Roche,Hristo Svilenov,Andreas Tosstorff,Matja Zalar,Robin Curtis,Jeremy P. Derrick,Wolfgang Frieß,Alexander P. Golovanov,Mikael Lund,Allan Nørgaard,Tarik A. Khan,Günther H.J. Peters,Alain Pluen,Dierk Roessner,Werner Streicher,Christopher F. van der Walle,Jim Warwicker,Shahid Uddin,Gerhard Winter,Jens Thostrup Bukrinski,Åsmund Rinnan,Pernille Harris
出处
期刊:Molecular Pharmaceutics [American Chemical Society]
卷期号:20 (6): 2951-2965
标识
DOI:10.1021/acs.molpharmaceut.3c00013
摘要

Therapeutic proteins can be challenging to develop due to their complexity and the requirement of an acceptable formulation to ensure patient safety and efficacy. To date, there is no universal formulation development strategy that can identify optimal formulation conditions for all types of proteins in a fast and reliable manner. In this work, high-throughput characterization, employing a toolbox of five techniques, was performed on 14 structurally different proteins formulated in 6 different buffer conditions and in the presence of 4 different excipients. Multivariate data analysis and chemometrics were used to analyze the data in an unbiased way. First, observed changes in stability were primarily determined by the individual protein. Second, pH and ionic strength are the two most important factors determining the physical stability of proteins, where there exists a significant statistical interaction between protein and pH/ionic strength. Additionally, we developed prediction methods by partial least-squares regression. Colloidal stability indicators are important for prediction of real-time stability, while conformational stability indicators are important for prediction of stability under accelerated stress conditions at 40 °C. In order to predict real-time storage stability, protein–protein repulsion and the initial monomer fraction are the most important properties to monitor.
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
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
1秒前
上官若男应助可爱的从寒采纳,获得10
2秒前
烂漫夜梅发布了新的文献求助10
3秒前
zzz发布了新的文献求助10
4秒前
4秒前
4秒前
汤汤完成签到,获得积分10
4秒前
yc发布了新的文献求助10
5秒前
彦夏完成签到,获得积分10
5秒前
6秒前
初柒发布了新的文献求助10
6秒前
董亦菲发布了新的文献求助10
6秒前
哈哈哈的一笑完成签到,获得积分10
7秒前
9秒前
10秒前
彭于彦祖应助科研通管家采纳,获得20
10秒前
小二郎应助科研通管家采纳,获得10
10秒前
传奇3应助科研通管家采纳,获得10
11秒前
花花发布了新的文献求助10
11秒前
11秒前
深情安青应助科研通管家采纳,获得10
11秒前
Orange应助科研通管家采纳,获得10
11秒前
马倩茹发布了新的文献求助10
11秒前
科研通AI5应助科研通管家采纳,获得10
11秒前
Hello应助科研通管家采纳,获得10
11秒前
wkjfh应助科研通管家采纳,获得10
11秒前
orixero应助科研通管家采纳,获得10
11秒前
科研通AI5应助科研通管家采纳,获得10
11秒前
香蕉觅云应助科研通管家采纳,获得10
12秒前
852应助科研通管家采纳,获得30
12秒前
SYLH应助科研通管家采纳,获得10
12秒前
丘比特应助科研通管家采纳,获得10
12秒前
酷波er应助科研通管家采纳,获得10
12秒前
12秒前
EasyNan应助科研通管家采纳,获得10
12秒前
Akim应助科研通管家采纳,获得10
12秒前
SYLH应助科研通管家采纳,获得10
12秒前
12秒前
爆米花应助科研通管家采纳,获得10
13秒前
oxo应助科研通管家采纳,获得10
13秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Animal Physiology 2000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Am Rande der Geschichte : mein Leben in China / Ruth Weiss 1500
CENTRAL BOOKS: A BRIEF HISTORY 1939 TO 1999 by Dave Cope 1000
Machine Learning Methods in Geoscience 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3740949
求助须知:如何正确求助?哪些是违规求助? 3283763
关于积分的说明 10036623
捐赠科研通 3000513
什么是DOI,文献DOI怎么找? 1646539
邀请新用户注册赠送积分活动 783771
科研通“疑难数据库(出版商)”最低求助积分说明 750427