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Related Concept Videos

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein-protein Interfaces02:04

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...
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...

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Related Experiment Video

Updated: Jun 18, 2026

Tandem Affinity Purification of Protein Complexes from Eukaryotic Cells
11:30

Tandem Affinity Purification of Protein Complexes from Eukaryotic Cells

Published on: January 26, 2017

Spectral affinity in protein networks.

Konstantin Voevodski1, Shang-Hua Teng, Yu Xia

  • 1Department of Computer Science, Boston University, Boston, MA 02215, USA. kvodski@bu.edu

BMC Systems Biology
|December 1, 2009
PubMed
Summary
This summary is machine-generated.

We introduce PageRank Affinity, a new method to measure protein closeness in protein-protein interaction networks. This approach accurately identifies functionally related proteins and is robust to noisy data.

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Tandem Affinity Purification of Protein Complexes from Eukaryotic Cells
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Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
14:58

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Published on: November 12, 2012

Area of Science:

  • Computational Biology
  • Network Science
  • Bioinformatics

Background:

  • Protein-protein interaction (PPI) networks are crucial for understanding proteome organization.
  • Analyzing protein neighborhoods in PPI networks helps identify proteins with similar functions.
  • Spectral methods using random walks offer robust and precise closeness measures in PPI networks.

Purpose of the Study:

  • To develop a novel and meaningful measure of protein closeness in PPI networks.
  • To improve the prediction of functional relationships and co-complex membership.
  • To create a scalable tool for querying protein proximity in biological networks.

Main Methods:

  • Developed a novel affinity measure called PageRank Affinity, based on personalized PageRank and random walks.
  • PageRank Affinity quantifies closeness by the visitation frequency of a lower-degree protein during a random walk starting from a higher-degree protein.
  • The method considers paths of all lengths, ensuring precision and robustness against network noise.

Main Results:

  • PageRank Affinity demonstrates superior performance in predicting co-complex membership compared to existing measures.
  • The measure effectively identifies functionally related proteins and is resilient to noise in PPI networks.
  • A scalable tool was developed for efficiently finding proteins closest to a query protein.

Conclusions:

  • PageRank Affinity provides a biologically significant method for assessing protein closeness in PPI networks.
  • This novel measure outperforms traditional methods in biological relevance and noise resilience.
  • A user-friendly tool is available for exploring protein proximity in biological networks.