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Related Experiment Videos

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

Alexander Jarasch1, Arne Skerra1

  • 1Munich Center for Integrated Protein Science (CiPSM) and Lehrstuhl für Biologische Chemie, Technische Universität München, Freising (Weihenstephan), Germany.

Proteins
|October 23, 2016
PubMed
Summary

Related Concept Videos

Antibody Structure01:10

Antibody Structure

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Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
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Antibody Structure and Classes01:25

Antibody Structure and Classes

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Antibodies, also known as immunoglobulins, are produced by B cells in response to foreign substances, such as bacteria and viruses. These proteins are critical for recognizing and neutralizing these substances, protecting the body from potential harm.
The basic structure of an antibody consists of four protein chains: two identical heavy chains and two identical light chains. These chains are held together by disulfide bonds and other non-covalent interactions, forming a Y-shaped structure.
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Analyzing immunoglobulin sequences is challenging. ANTICALIgN uses pattern matching to automatically identify antibody regions, simplifying antibody engineering and analysis.

Area of Science:

  • Immunology
  • Bioinformatics
  • Computational Biology

Background:

  • Analyzing large immunoglobulin (Ig) sequence datasets for antibody selection is complex and manual.
  • Standardized numbering schemes for Ig framework and complementarity-determining regions (CDRs) require expert knowledge and can be limited by CDR length variability.
  • Existing sequence alignment editors lack algorithms for automatic annotation of new Ig sequences.

Purpose of the Study:

  • To develop an automated method for identifying and annotating antibody sequence regions.
  • To introduce the ANTICALIgN editor and its pattern-matching capabilities for antibody engineering.

Main Methods:

  • Implementation of a unique pattern matching method using regular expressions within the ANTICALIgN editor.
  • Development of real-time aligning, editing, and analyzing capabilities for extended sets of amino acid and/or nucleotide sequences.
Keywords:
amino acid sequencecomplementarity-determining regionconsensus sequencehypervariable regionpattern searchprotein designprotein scaffold

Related Experiment Videos

Main Results:

  • The ANTICALIgN editor automatically identifies hypervariable and framework regions in antibody sequences.
  • The software facilitates simultaneous analysis of multiple sequences on a local workstation.

Conclusions:

  • ANTICALIgN offers a powerful and efficient utility for antibody engineering.
  • Automated annotation of Ig sequences simplifies analysis and reduces the need for manual intervention.