ANARCI: antigen receptor numbering and receptor classification

Dunbar, James B.; Deane, Charlotte M.

doi:10.1093/bioinformatics/btv552

Cited by 262 publications

(253 citation statements)

References 12 publications

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“…We used the 242 antibodies from Raybould et al 14 as the source of Clinical Stage Therapeutic (CST) antibodies. We numbered the CST sequences according to the IMGT 28 scheme using ANARCI 29 . The CST sequences were classified into four groups, based on their International Nonproprietary Names 15,30 .…”

Section: Methodsmentioning

confidence: 99%

Looking for Therapeutic Antibodies in Next Generation Sequencing Repositories

Krawczyk¹,

Kovaltsuk

Raybould

et al. 2019

Preprint

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Recently it has become possible to query the great diversity of natural antibody repertoires using Next Generation Sequencing (NGS). These methods are capable of producing millions of sequences in a single experiment. Here we compare Clinical Stage Therapeutic antibodies to the ~1b sequences from 60 independent sequencing studies in the Observed Antibody Space Database. Of the 242 post Phase I antibodies, we find 16 with sequence identity matches of 95% or better for both heavy and light chains. There are also 54 perfect matches to therapeutic CDR-H3 regions in the NGS outputs, suggesting a nontrivial amount of convergence between naturally observed sequences and those developed artificially. This has potential implications for both the discovery of antibody therapeutics and the legal protection of commercial antibodies.

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Section: Methodsmentioning

confidence: 99%

Looking for Therapeutic Antibodies in Next Generation Sequencing Repositories

Krawczyk¹,

Kovaltsuk

Raybould

et al. 2019

Preprint

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“…such as quoted further above or to match more peculiar Ig (sub)classes. This abolishes the need for external computing servers that have been established to facilitate CDR assignment in antibody sequences …”

Section: Discussionmentioning

confidence: 99%

“…This abolishes the need for external computing servers that have been established to facilitate CDR assignment in antibody sequences. 26 In general, such search patterns provide a simple way to investigate any interesting feature in a given amino acid or nucleotide sequence, even beyond the area of antibody engineering. The regular expressions follow a simple syntax and can be defined as search query by the user to fit individual purposes.…”

Section: Discussionmentioning

confidence: 99%

Aligning, analyzing, and visualizing sequences for antibody engineering: Automated recognition of immunoglobulin variable region features

Jarasch

Skerra

2016

Proteins

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The analysis and comparison of large numbers of immunoglobulin (Ig) sequences that arise during an antibody selection campaign can be time-consuming and tedious. Typically, the identification and annotation of framework as well as complementarity-determining regions (CDRs) is based on multiple sequence alignments using standardized numbering schemes, which allow identification of equivalent residues among different family members but often necessitate expert knowledge and manual intervention. Moreover, due to the enormous length variability of some CDRs the benefit of conventional Ig numbering schemes is limited and the calculation of correct sequence alignments can become challenging. Whereas, in principle, a well established set of rules permits the assignment of CDRs from the amino acid sequence alone, no currently available sequence alignment editor provides an algorithm to annotate new Ig sequences accordingly. Here we present a unique pattern matching method implemented into our recently developed ANTICALIgN editor that automatically identifies all hypervariable and framework regions in experimentally elucidated antibody sequences using so-called "regular expressions." By combination of this widely supported software syntax with the unique capabilities of real-time aligning, editing and analyzing extended sets of amino acid and/or nucleotide sequences simultaneously on a local workstation, ANTICALIgN provides a powerful utility for antibody engineering. Proteins 2016; 85:65-71. © 2016 Wiley Periodicals, Inc.

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“…CDR modellability analysis. Each sequence was first numbered using ANARCI (35) Predicting modellable VH-VL orientations. The 20 most important VH-VL interface residues for orientation prediction were derived; a sequence identity of 85% over these 20 residues resulted in an orientation RMSD of ≤ 1.5Å ∼ 80% of the time (see SI Methods).…”

Section: Methodsmentioning

confidence: 99%

Evidence of Antibody Repertoire Functional Convergence through Public Baseline and Shared Response Structures

Raybould¹,

Marks²,

Kovaltsuk³

et al. 2020

Preprint

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The antibody repertoires of different individuals ought to exhibit significant functional commonality, given that most pathogens trigger a successful immune response in most people. Sequence-based approaches have so far offered little evidence for this phenomenon. For example, a recent study estimated the number of shared ('public') antibody clonotypes in circulating baseline repertoires to be around 0.02% across ten unrelated individuals. However, to engage the same epitope, antibodies only require a similar binding site structure and the presence of key paratope interactions, which can occur even when their sequences are dissimilar. Here, we investigate functional convergence in human antibody repertoires by comparing the antibody structures they contain. We first structurally profile baseline antibody diversity (using snapshots from 41 unrelated individuals), predicting all modellable distinct structures within each repertoire. This analysis uncovers a high degree of structural commonality. For instance, around 3% of distinct structures are common to the ten most diverse individual samples ('Public Baseline' structures). Our approach is the first computational method to provide support for the long-assumed levels of baseline repertoire functional commonality. We then apply the same structural profiling approach to repertoire snapshots from three individuals before and after flu vaccination, detecting a convergent structural drift indicative of recognising similar epitopes ('Public Response' structures). Antibody Model Libraries (AMLs) derived from Public Baseline and Public Response structures represent a powerful geometric basis set of low-immunogenicity candidates exploitable for general or target-focused therapeutic antibody screening. antibody repertoire | structural profiling | public structures | antibody model libraries | antibody screening Correspondence: deane@stats.ox.ac.uk

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ANARCI: antigen receptor numbering and receptor classification

Cited by 262 publications

References 12 publications

Looking for Therapeutic Antibodies in Next Generation Sequencing Repositories

Looking for Therapeutic Antibodies in Next Generation Sequencing Repositories

Aligning, analyzing, and visualizing sequences for antibody engineering: Automated recognition of immunoglobulin variable region features

Evidence of Antibody Repertoire Functional Convergence through Public Baseline and Shared Response Structures

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