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本文引用的文献

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Establishing in vitro in vivo correlations to screen monoclonal antibodies for physicochemical properties related to favorable human pharmacokinetics.建立体外-体内相关性以筛选与良好人体药代动力学相关的物理化学性质的单克隆抗体。
MAbs. 2018 Feb/Mar;10(2):244-255. doi: 10.1080/19420862.2017.1417718. Epub 2018 Jan 29.
2
Reduction of Nonspecificity Motifs in Synthetic Antibody Libraries.合成抗体库中非特异性基序的减少
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Biophysical and Sequence-Based Methods for Identifying Monovalent and Bivalent Antibodies with High Colloidal Stability.基于生物物理和序列的方法鉴定具有高胶体稳定性的单价和双价抗体。
Mol Pharm. 2018 Jan 2;15(1):150-163. doi: 10.1021/acs.molpharmaceut.7b00779. Epub 2017 Dec 6.
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Facile Affinity Maturation of Antibody Variable Domains Using Natural Diversity Mutagenesis.利用自然多样性诱变实现抗体可变区的简便亲和力成熟
Front Immunol. 2017 Sep 4;8:986. doi: 10.3389/fimmu.2017.00986. eCollection 2017.
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Nonspecificity in a nonimmune human scFv repertoire.非免疫的人 scFv 文库中的非特异性。
MAbs. 2017 Oct;9(7):1029-1035. doi: 10.1080/19420862.2017.1356528. Epub 2017 Sep 14.
6
Arginine mutations in antibody complementarity-determining regions display context-dependent affinity/specificity trade-offs.抗体互补决定区中的精氨酸突变表现出依赖于上下文的亲和力/特异性权衡。
J Biol Chem. 2017 Oct 6;292(40):16638-16652. doi: 10.1074/jbc.M117.783837. Epub 2017 Aug 4.
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Chaperone proteins as single component reagents to assess antibody nonspecificity.伴侣蛋白作为单一成分试剂来评估抗体的非特异性。
MAbs. 2017 Oct;9(7):1036-1040. doi: 10.1080/19420862.2017.1356529. Epub 2017 Jul 26.
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Biophysical properties of the clinical-stage antibody landscape.临床阶段抗体格局的生物物理特性。
Proc Natl Acad Sci U S A. 2017 Jan 31;114(5):944-949. doi: 10.1073/pnas.1616408114. Epub 2017 Jan 17.
9
Engineering the surface properties of a human monoclonal antibody prevents self-association and rapid clearance in vivo.工程化人源单克隆抗体的表面特性可防止其在体内发生自身聚集和快速清除。
Sci Rep. 2016 Dec 20;6:38644. doi: 10.1038/srep38644.
10
Facile Preparation of Stable Antibody-Gold Conjugates and Application to Affinity-Capture Self-Interaction Nanoparticle Spectroscopy.稳定抗体-金缀合物的简便制备及其在亲和捕获自相互作用纳米颗粒光谱中的应用。
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抗体互补决定区的净电荷是特异性的关键预测指标。

Net charge of antibody complementarity-determining regions is a key predictor of specificity.

作者信息

Rabia Lilia A, Zhang Yulei, Ludwig Seth D, Julian Mark C, Tessier Peter M

机构信息

Isermann Department of Chemical & Biological Engineering, Center for Biotechnology & Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, USA.

Department of Pharmaceutical Sciences.

出版信息

Protein Eng Des Sel. 2018 Nov 1;31(11):409-418. doi: 10.1093/protein/gzz002.

DOI:10.1093/protein/gzz002
PMID:30770934
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6524611/
Abstract

Specificity is one of the most important and complex properties that is central to both natural antibody function and therapeutic antibody efficacy. However, it has proven extremely challenging to define robust guidelines for predicting antibody specificity. Here we evaluated the physicochemical determinants of antibody specificity for multiple panels of antibodies, including >100 clinical-stage antibodies. Surprisingly, we find that the theoretical net charge of the complementarity-determining regions (CDRs) is a strong predictor of antibody specificity. Antibodies with positively charged CDRs have a much higher risk of low specificity than antibodies with negatively charged CDRs. Moreover, the charge of the entire set of six CDRs is a much better predictor of antibody specificity than the charge of individual CDRs, variable domains (VH or VL) or the entire variable fragment (Fv). The best indicators of antibody specificity in terms of CDR amino acid composition are reduced levels of arginine and lysine and increased levels of aspartic and glutamic acid. Interestingly, clinical-stage antibodies with negatively charged CDRs also have a lower risk for poor biophysical properties in general, including a reduced risk for high levels of self-association. These findings provide powerful guidelines for predicting antibody specificity and for identifying safe and potent antibody therapeutics.

摘要

特异性是自然抗体功能和治疗性抗体疗效的核心,是最重要且复杂的特性之一。然而,事实证明,制定预测抗体特异性的可靠指南极具挑战性。在此,我们评估了多组抗体(包括100多种临床阶段抗体)的抗体特异性的物理化学决定因素。令人惊讶的是,我们发现互补决定区(CDR)的理论净电荷是抗体特异性的有力预测指标。与带负电荷CDR的抗体相比,带正电荷CDR的抗体具有低特异性的风险要高得多。此外,整套六个CDR的电荷比单个CDR、可变结构域(VH或VL)或整个可变片段(Fv)的电荷更能预测抗体特异性。就CDR氨基酸组成而言,抗体特异性的最佳指标是精氨酸和赖氨酸水平降低以及天冬氨酸和谷氨酸水平升高。有趣的是,一般而言,带负电荷CDR的临床阶段抗体具有较差生物物理特性的风险也较低,包括高水平自我缔合风险降低。这些发现为预测抗体特异性以及鉴定安全有效的抗体疗法提供了有力指南。