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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...
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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
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PICI: A web server with a multi-parametric algorithm for identifying interaction sites within protein complexes.

Arindam Atanu Das1, Ramadas Krishna1

  • 1Centre for Bioinformatics, Pondicherry University, Puducherry 605014, India.

Bioinformation
|January 21, 2017
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Summary

The Protein Inter-chain Interaction (PICI) server identifies protein interactions using the Protein Interaction Identification Algorithm (PIIA). It offers advanced visualization tools for analyzing protein complex stability and function.

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Bioinformatics

Background:

  • Understanding protein-protein interactions is crucial for deciphering cellular functions and structural integrity.
  • Existing computational tools require enhancement for comprehensive analysis of protein interfaces.

Purpose of the Study:

  • To introduce the Protein Inter-chain Interaction (PICI) server for identifying protein interaction sites and analyzing inter-chain interactions.
  • To present the Protein Interaction Identification Algorithm (PIIA) as the core engine of the PICI server.

Main Methods:

  • The PICI server utilizes the Protein Interaction Identification Algorithm (PIIA), a multi-parametric approach.
  • PIIA considers interface area, atomic distances, bond linearity, aromatic side-chain orientation, and residue physicochemical properties.
  • The server accepts PDBids or uploaded structure files for analysis.

Main Results:

  • PICI can identify a wide range of protein interactions, including novel weak and strong interactions.
  • The server provides diverse data representations: text tables, 3D visualization, sequence viewer, and graphical matrix.
  • Results are downloadable in plain text or XML formats.

Conclusions:

  • The PICI server offers a distinct and comprehensive platform for analyzing protein-protein interactions.
  • Its advanced features and visualization tools facilitate a deeper understanding of protein complex dynamics and function.