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Related Concept Videos

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...
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...
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,...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
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...

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Related Experiment Video

Updated: Jun 18, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Local optimization for global alignment of protein interaction networks.

Leonid Chindelevitch1, Chung-Shou Liao, Bonnie Berger

  • 1Department of Mathematics and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. leonidus@csail.mit.edu

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|November 13, 2009
PubMed
Summary

We introduce PISwap, a new algorithm for aligning protein interaction networks. This method improves upon sequence alignment by integrating network structure, offering better results and evolutionary insights.

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Last Updated: Jun 18, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling
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Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling

Published on: October 7, 2021

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells
08:38

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells

Published on: March 3, 2015

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Protein interaction networks are crucial for understanding cellular processes.
  • Aligning these networks is vital for comparative analysis and inferring function.
  • Existing methods often struggle with the complexity and scale of biological networks.

Purpose of the Study:

  • To develop a novel algorithm for global pairwise alignment of protein interaction networks.
  • To improve the accuracy and efficiency of network alignment compared to existing methods.
  • To provide a flexible tool for various network alignment applications and evolutionary studies.

Main Methods:

  • The PISwap algorithm utilizes a local optimization heuristic, similar to those used for the Traveling Salesman Problem.
  • It starts with a sequence-based network alignment.
  • The alignment is iteratively refined by incorporating network topology information.

Main Results:

  • PISwap demonstrates a pseudo-polynomial worst-case running-time bound and high practical efficiency.
  • The algorithm produces improved alignments in several well-studied biological network cases.
  • It offers flexibility for diverse network alignment tasks.

Conclusions:

  • PISwap is an effective and efficient algorithm for global pairwise alignment of protein interaction networks.
  • The integration of network structure information leads to enhanced alignment accuracy.
  • The method provides valuable insights into the evolutionary relationships between species based on their interactomes.