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Protein Organization

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.
The primary structure of a protein is its amino acid sequence.

Protein Organization

Protein Organization

Protein Organization

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.
The primary structure of a protein is its amino acid sequence.

Protein Organization

Protein Organization

Protein-protein Interfaces

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 Interfaces

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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Related Experiment Video

Updated: Jul 6, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

PSAIA - protein structure and interaction analyzer.

Josip Mihel¹, Mile Sikić, Sanja Tomić

¹Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia. josip.mihel@fer.hr

BMC Structural Biology

|April 11, 2008

Summary

Protein Structure and Interaction Analyzer (PSAIA) computes geometric parameters for protein structures to predict interaction sites. Its new PIADA method enhances residue interaction pair determination, improving analysis of large datasets.

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Last Updated: Jul 6, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

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Area of Science:

Structural Biology
Computational Biology
Bioinformatics

Background:

Protein Structure and Interaction Analyzer (PSAIA) was developed to compute geometric parameters for large sets of protein structures.
The primary goal was to predict and investigate protein-protein interaction sites.

Purpose of the Study:

To introduce PSAIA and its novel Protein Interaction Atom Distance Algorithm (PIADA).
To evaluate PSAIA's capability in analyzing large protein structure datasets for interaction site prediction.

Main Methods:

PSAIA integrates established algorithms with a new method, PIADA, for residue interaction pair determination.
The software handles large numbers of protein structures and complexes without further automation.
Analysis can be performed via a graphical user interface or command-line, with results in tabular or XML format.

Main Results:

PIADA demonstrated more satisfactory results compared to other algorithms within PSAIA.
PSAIA effectively combines multiple methods for detecting interaction locations and types.
The software facilitates automated analysis and enhances the reliability of results for large datasets.

Conclusions:

PSAIA enables straightforward calculation of protein geometric parameters and determination of protein-protein interaction sites for large datasets.
XML output facilitates statistical analysis of results.
Analysis of large datasets using PSAIA provides new insights for predicting protein-protein interaction sites.