抗体
同型
药物发现
药品
计算机科学
构造(python库)
财产(哲学)
计算生物学
免疫学
生物信息学
药理学
单克隆抗体
生物
认识论
哲学
程序设计语言
作者
Tushar Jain,Tingwan Sun,Stéphanie Durand,Amy Hall,Nga Rewa Houston,Juergen H. Nett,Beth Sharkey,Beata Bobrowicz,Isabelle Caffry,Yao Yu,Yuan Cao,Heather Lynaugh,Michael E. Brown,Hemanta Baruah,Laura Gray,Eric Krauland,Yingda Xu,Maximiliano Vásquez,K. Dane Wittrup
标识
DOI:10.1073/pnas.1616408114
摘要
Antibodies are a highly successful class of biological drugs, with over 50 such molecules approved for therapeutic use and hundreds more currently in clinical development. Improvements in technology for the discovery and optimization of high-potency antibodies have greatly increased the chances for finding binding molecules with desired biological properties; however, achieving drug-like properties at the same time is an additional requirement that is receiving increased attention. In this work, we attempt to quantify the historical limits of acceptability for multiple biophysical metrics of "developability." Amino acid sequences from 137 antibodies in advanced clinical stages, including 48 approved for therapeutic use, were collected and used to construct isotype-matched IgG1 antibodies, which were then expressed in mammalian cells. The resulting material for each source antibody was evaluated in a dozen biophysical property assays. The distributions of the observed metrics are used to empirically define boundaries of drug-like behavior that can represent practical guidelines for future antibody drug candidates.
科研通智能强力驱动
Strongly Powered by AbleSci AI