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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 and Protein Structure

Protein and Protein Structure

Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme can...

Conservation of Protein Domains Over Different Proteins

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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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

SANA: an algorithm for sequential and non-sequential protein structure alignment.

Lin Wang¹, Ling-Yun Wu, Yong Wang

¹Computer Science and Information Engineering College, Tianjin University of Science and Technology, Tianjin, 300222, China. juanzi_1982_49@126.com

|February 4, 2010

Summary

A new protein structure alignment method accurately identifies similarities, even with internal repeats or gaps. This novel approach refines alignments using multi-objective optimization, outperforming existing algorithms in biological significance.

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Area of Science:

Computational biology
Structural bioinformatics
Bioinformatics algorithms

Background:

Protein structure alignment is crucial for understanding protein function and evolution.
Existing algorithms face challenges with complex structures, including internal repeats and insertions/deletions (indels).

Purpose of the Study:

To present a novel, robust protein structure alignment algorithm.
To improve accuracy and biological relevance in structure-based comparisons.
To handle challenging cases like internal repeats, indels, and circular permutations.

Main Methods:

Core regions of protein structures are aligned using connected components in a network of compatible fragment pairs.
Initial alignments are refined via a multi-objective optimization technique.
The algorithm generates both sequential and non-sequential alignments.

Main Results:

The proposed algorithm demonstrates superior performance on benchmark datasets compared to DALI, CE, and MATT.
Accurate and biologically significant alignments are achieved, even with internal repeats and indels.
The method successfully identifies circular permutations and conserved functional sites.
A novel ranking criterion for fold similarity is comparable or superior to existing metrics like CE's Z-score.

Conclusions:

The novel structure alignment algorithm offers enhanced accuracy and biological insight.
It effectively addresses limitations of previous methods, particularly in complex structural scenarios.
The developed tool provides a valuable resource for structural bioinformatics research.