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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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.
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Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
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Signal Sequences and Sorting Receptors

Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
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Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...
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Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
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Peptide-based Identification of Functional Motifs and their Binding Partners
14:28

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

A motif detection and classification method for peptide sequences using genetic programming.

Yasuyuki Tomita1, Ryuji Kato, Mina Okochi

  • 1Department of Biotechnology, School of Engineering, Nagoya University, Nagoya, Japan.

Journal of Bioscience and Bioengineering
|September 23, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a novel genetic programming (GP) method to identify common property motifs in peptide sequences. The approach effectively discovers functional peptide aspects and enhances MHC class II binding peptide identification.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Designing novel amino acid sequences requires understanding common rules, or property motifs.
  • Elucidating molecular interactions necessitates knowledge of sequence-based property motifs influenced by the environment.

Purpose of the Study:

  • To develop a new method for searching common property motifs in peptide sequence data.
  • To automatically determine the position and length of property motifs by assessing amino acid physicochemical similarity.
  • To efficiently explore motif candidates using genetic programming (GP) for improved discrimination.

Main Methods:

  • Developed a novel algorithm combining physicochemical similarity calculations with genetic programming (GP).
  • Algorithm automatically determines motif position and length.
  • Utilized GP for rapid and effective exploration and discrimination of motif candidates.

Main Results:

  • Successfully extracted intentionally buried property motifs from artificial peptide data.
  • Identified twofold more MHC class II binding peptides compared to existing scoring matrix methods.
  • Demonstrated the method's efficacy in analyzing biologically active peptides with varying motif lengths.

Conclusions:

  • The GP-based motif searching approach provides insights into peptide functional aspects without prior knowledge.
  • This method offers a significant improvement over existing techniques for identifying functionally relevant sequence motifs.
  • The study highlights the potential of GP in advancing peptide sequence analysis and design.