Literature DB >> 31020723

AbRSA: A robust tool for antibody numbering.

Lei Li1, Shuang Chen2, Zhichao Miao3,4, Yang Liu1, Xu Liu1, Zhi-Xiong Xiao1, Yang Cao1,5.   

Abstract

The remarkable progress in cancer immunotherapy in recent years has led to the heat of great development for therapeutic antibodies. Antibody numbering, which standardizes a residue index at each position of an antibody variable domain, is an important step in immunoinformatic analysis. It provides an equivalent index for the comparison of sequences or structures, which is particularly valuable for antibody modeling and engineering. However, due to the extremely high diversity of antibody sequences, antibody-numbering tools cannot work in all cases. This article introduces a new antibody-numbering tool named AbRSA, which integrates heuristic knowledge of region-specific features into sequence mapping to enhance the robustness. The benchmarks demonstrate that, AbRSA exhibits robust performance in numbering sequences with diverse lengths and patterns compared with the state-of-the-art tools. AbRSA offers a user-friendly interface for antibody numbering, complementarity-determining region delimitation, and 3D structure rendering. It is freely available at http://cao.labshare.cn/AbRSA.
© 2019 The Protein Society.

Entities:  

Keywords:  antibody; antibody numbering; complementarity-determining region; immunoinformatic

Mesh:

Substances:

Year:  2019        PMID: 31020723      PMCID: PMC6635766          DOI: 10.1002/pro.3633

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  37 in total

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Review 3.  Central Nervous System Delivery of Antibodies and Their Single-Domain Antibodies and Variable Fragment Derivatives with Focus on Intranasal Nose to Brain Administration.

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6.  Prediction of HIV Sensitivity to Monoclonal Antibodies Using Aminoacid Sequences and Deep Learning.

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7.  Computational approaches to therapeutic antibody design: established methods and emerging trends.

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