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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
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Epitope identification from fixed-complexity random-sequence peptide microarrays.

Josh Richer1, Stephen Albert Johnston1, Phillip Stafford2

  • 1From *Arizona State University, Tempe, Arizona 85287.

Molecular & Cellular Proteomics : MCP
|November 5, 2014
PubMed
Summary
This summary is machine-generated.

Researchers developed a low-cost peptide microarray platform for rapid antibody epitope mapping. This unbiased method identified epitopes for monoclonal antibodies and potential antigens in infectious disease cohorts, enhancing antigen discovery.

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Area of Science:

  • Biochemistry
  • Immunology
  • Bioinformatics

Background:

  • Antibodies are crucial in biological assays and therapeutics.
  • Current epitope mapping methods are costly and lack universal platforms.
  • There is a need for accessible and efficient antibody epitope identification tools.

Purpose of the Study:

  • To develop and validate a low-cost, universal platform for antibody epitope mapping.
  • To create an algorithm for analyzing random-sequence peptide microarrays for epitope identification.
  • To assess the platform's efficacy in identifying epitopes for monoclonal antibodies and infectious disease antigens.

Main Methods:

  • Utilized a random-sequence peptide microarray with over 330,000 unique sequences.
  • Developed a novel algorithm to analyze k-mer significance within microarray peptides.
  • Tested the platform with eight monoclonal antibodies and seven infectious disease cohorts.

Main Results:

  • Successfully identified epitopes for five out of eight tested monoclonal antibodies.
  • Detected both known and novel epitope candidates in infectious disease cohorts.
  • Demonstrated the platform's unbiased nature and independence from proteome-specific informatics.

Conclusions:

  • The random-sequence peptide microarray offers a cost-effective and universal solution for epitope mapping.
  • The developed algorithm significantly enhances the utility of peptide microarrays for antigen discovery.
  • This approach promises to accelerate research in antibody development and infectious disease diagnostics.