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Protein Families

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism. Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members. If these new proteins contain similar amino acids in key locations, protein...

Protein Families

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism. Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members. If these new proteins contain similar amino acids in key locations, protein...

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...

Protein Networks

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 Networks

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 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...

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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

Protein functional class prediction using global encoding of amino acid sequence.

Xi Li¹, Bo Liao, Yu Shu

¹School of Computer and Communication, Hunan University, Changsha Hunan 410082, China.

Journal of Theoretical Biology

|July 28, 2009

Summary

We developed a global encoding (GE) method to predict protein function using machine learning. This approach improves accuracy over existing methods for classifying unknown protein functions.

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Area of Science:

Bioinformatics
Computational Biology
Proteomics

Background:

Determining protein function is crucial in the post-genomic era.
Accurate protein functional classification aids biological research and drug discovery.

Purpose of the Study:

To propose a novel global encoding (GE) method for protein sequence analysis.
To enhance the prediction accuracy of protein functional classes using machine learning.

Main Methods:

Developed a global encoding (GE) method to capture global amino acid sequence information.
Applied the nearest neighbor algorithm (NNA) for protein functional classification.
Predicted functions for 1818 Saccharomyces cerevisiae proteins.

Main Results:

The GE method demonstrated improved predictive accuracy compared to Vazquez's global optimization method (GOM) in certain cases.
The approach proved efficient for classifying the functional class of unknown proteins.

Conclusions:

The proposed global encoding (GE) method is an effective tool for predicting protein function.
This method offers a valuable advancement in computational approaches for functional genomics.