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Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
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Protein-Protein Interfaces02:04

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Updated: May 23, 2026

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics
12:53

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics

Published on: July 6, 2014

Mining literature for protein-protein interactions.

E M Marcotte1, I Xenarios, D Eisenberg

  • 1Molecular Biology Institute, UCLA-DOE Laboratory of Structural Biology & Molecular Medicine, University of California at Los Angeles, PO Box 951570, Los Angeles, CA 90095-1570, USA.

Bioinformatics (Oxford, England)
|April 13, 2001
PubMed
Summary

This study uses word frequencies in Medline abstracts to identify papers discussing protein-protein interactions. This method aids in expanding the Database of Interacting Proteins with relevant scientific information.

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Last Updated: May 23, 2026

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Scientific Literature Analysis

Background:

  • Extracting information from scientific literature for computational analysis is a key bioinformatics challenge.
  • Focuses on protein-protein interactions, a critical area in molecular biology.
  • Existing methods struggle to process the volume of scientific publications.

Purpose of the Study:

  • To develop a computational method for identifying scientific papers that discuss protein-protein interactions.
  • To enable automated capture of protein-protein interaction data for databases.
  • To facilitate the expansion of the Database of Interacting Proteins.

Main Methods:

  • Utilized word frequencies within Medline abstracts to classify relevant papers.
  • Developed a Bayesian approach to score abstracts based on discriminating word occurrences.
  • Identified over 80 discriminating words (e.g., 'complex', 'interaction', 'two-hybrid') from a training set.

Main Results:

  • Successfully identified approximately 2000 Medline abstracts detailing yeast protein interactions.
  • The word frequency analysis demonstrated high accuracy in detecting relevant scientific literature.
  • The approach is now foundational for the rapid growth of the Database of Interacting Proteins.

Conclusions:

  • Word frequency analysis of Medline abstracts is an effective strategy for identifying protein-protein interaction literature.
  • This computational approach significantly enhances the ability to curate and expand protein interaction databases.
  • Automated literature mining accelerates the discovery and accessibility of crucial biological data.