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使用免疫球蛋白结构预测 (PIGS) 网络服务器进行抗体建模 [更正]。

Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected].

机构信息

Physics Department, Sapienza University of Rome, Piazzale Aldo Moro, Rome, Italy.

1] Physics Department, Sapienza University of Rome, Piazzale Aldo Moro, Rome, Italy. [2] Istituto Pasteur - Fondazione Cenci Bolognetti, Sapienza University of Rome, Rome, Italy.

出版信息

Nat Protoc. 2014 Dec;9(12):2771-83. doi: 10.1038/nprot.2014.189. Epub 2014 Nov 6.

DOI:10.1038/nprot.2014.189
PMID:25375991
Abstract

Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

摘要

抗体(或免疫球蛋白)对于保护生物体免受病原体侵害至关重要,但它们也是许多医学、诊断和生物技术应用中的关键因素。能够预测其结构以及参与抗原识别的特定残基在所有这些领域都有几个有用的应用。多年来,我们开发或合作开发了一种策略,使研究人员能够以非常令人满意的准确度预测抗体的 3D 结构。该策略完全自动化,速度极快,构建抗体结构模型仅需几分钟(平均约 10 分钟)。它基于抗体环的规范结构概念和我们对轻链和重链包装方式的理解。

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2
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Proteins. 2014 Aug;82(8):1624-35. doi: 10.1002/prot.24591. Epub 2014 May 13.
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Second antibody modeling assessment (AMA-II).
抗体和 T 细胞受体(CDR3 环)的计算建模。
Methods Mol Biol. 2023;2552:83-100. doi: 10.1007/978-1-0716-2609-2_3.
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