Aligning, analyzing, and visualizing sequences for antibody engineering: Automated recognition of immunoglobulin variable region features
ABSTRACT 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 multi...
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Veröffentlicht in: | Proteins, structure, function, and bioinformatics structure, function, and bioinformatics, 2017-01, Vol.85 (1), p.65-71 |
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description | ABSTRACT
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. |
doi_str_mv | 10.1002/prot.25193 |
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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.</description><identifier>ISSN: 0887-3585</identifier><identifier>EISSN: 1097-0134</identifier><identifier>DOI: 10.1002/prot.25193</identifier><identifier>PMID: 27770557</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Algorithms ; Amino Acid Sequence ; Animals ; Antibodies - chemistry ; Base Sequence ; Complementarity Determining Regions - analysis ; complementarity‐determining region ; Computational Biology - methods ; consensus sequence ; Humans ; hypervariable region ; Models, Molecular ; pattern search ; protein design ; Protein Engineering ; protein scaffold ; Sequence Alignment ; Software</subject><ispartof>Proteins, structure, function, and bioinformatics, 2017-01, Vol.85 (1), p.65-71</ispartof><rights>2016 Wiley Periodicals, Inc.</rights><rights>2017 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3903-8c4c0c6f59c07ed29ebd29d2bfc75f22f9f6c9f0afbc6f0848793a901a74d5333</citedby><cites>FETCH-LOGICAL-c3903-8c4c0c6f59c07ed29ebd29d2bfc75f22f9f6c9f0afbc6f0848793a901a74d5333</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fprot.25193$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fprot.25193$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27770557$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jarasch, Alexander</creatorcontrib><creatorcontrib>Skerra, Arne</creatorcontrib><title>Aligning, analyzing, and visualizing sequences for antibody engineering: Automated recognition of immunoglobulin variable region features</title><title>Proteins, structure, function, and bioinformatics</title><addtitle>Proteins</addtitle><description>ABSTRACT
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. 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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.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>27770557</pmid><doi>10.1002/prot.25193</doi><tpages>7</tpages></addata></record> |
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subjects | Algorithms Amino Acid Sequence Animals Antibodies - chemistry Base Sequence Complementarity Determining Regions - analysis complementarity‐determining region Computational Biology - methods consensus sequence Humans hypervariable region Models, Molecular pattern search protein design Protein Engineering protein scaffold Sequence Alignment Software |
title | Aligning, analyzing, and visualizing sequences for antibody engineering: Automated recognition of immunoglobulin variable region features |
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