Computational tool for the early screening of monoclonal antibodies for their viscosities
Computational tool for the early screening of monoclonal antibodies for their viscosities
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DOI：
10.1080/19420862.2015.1099773
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发表时间：
2016-01-02
期刊：
影响因子：
5.3
通讯作者：
Trout, Bernhardt L.
中科院分区：
文献类型：
--
作者：
Agrawal, Neeraj J.;Helk, Bernhard;Trout, Bernhardt L.
高浓度抗体溶液通常表现出高粘度，这对抗体-药物开发、制造和施用提出了许多挑战。抗体序列是高浓度溶液的高粘度的关键决定因素;因此，可以从其序列中识别高粘度抗体的基于序列或结构的工具将有效地确保仅具有低粘度的抗体进入开发阶段。在这里，我们提出了一个空间电荷图（SCM）工具，可以准确地识别高粘性抗体从他们的序列单独（使用同源建模，以确定三维结构）。SCM工具已在3个不同的组织中得到广泛验证，并已证明在正确识别高粘性抗体方面是成功的。作为一种定量工具，SCM适合于高通量自动化分析，并且可以在抗体筛选或工程化阶段有效地实施，以选择低粘度抗体。
Highly concentrated antibody solutions often exhibit high viscosities, which present a number of challenges for antibody-drug development, manufacturing and administration. The antibody sequence is a key determinant for high viscosity of highly concentrated solutions; therefore, a sequence- or structure-based tool that can identify highly viscous antibodies from their sequence would be effective in ensuring that only antibodies with low viscosity progress to the development phase. Here, we present a spatial charge map (SCM) tool that can accurately identify highly viscous antibodies from their sequence alone (using homology modeling to determine the 3-dimensional structures). The SCM tool has been extensively validated at 3 different organizations, and has proved successful in correctly identifying highly viscous antibodies. As a quantitative tool, SCM is amenable to high-throughput automated analysis, and can be effectively implemented during the antibody screening or engineering phase for the selection of low-viscosity antibodies.