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Related Concept Videos

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,...
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 Families02:47

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 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...
Protein Organization01:24

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.

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A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

A novel neural response algorithm for protein function prediction.

Hari Krishna Yalamanchili1, Quan-Wu Xiao, Junwen Wang

  • 1Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.

BMC Systems Biology
|October 11, 2012
PubMed
Summary

A new automated protein function prediction method uses a neural response algorithm to improve accuracy. This approach enhances gene annotation by identifying remote homologues, achieving 86.93% accuracy in predicting Gene Ontology terms.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput genome sequencing generates vast data, outpacing experimental functional characterization.
  • Existing automated annotation methods struggle with low sequence coverage and detecting remote homologues.
  • There is a critical need for improved automated protein function prediction methods with higher accuracy and specificity.

Purpose of the Study:

  • To develop a novel automated protein functional assignment method.
  • To address the limitations of existing methods in sequence coverage and annotation specificity.
  • To enhance the accuracy of protein function prediction.

Main Methods:

  • Designed a novel automated protein functional assignment method based on a neural response algorithm.
  • Simulated neuronal behavior of the human visual cortex to predict protein similarity.
  • Utilized Hidden Markov Model (HMM) profiles and secondary structure information.

Main Results:

  • The method successfully predicted the correct leaf Gene Ontology (GO) term among the top 5 probable GO terms.
  • Achieved a high accuracy of 86.93% on the test set.
  • Demonstrated prominent performance compared to existing servers like PFP and FFPred through 5-fold cross-validation.

Conclusions:

  • The proposed neural response algorithm is the first of its kind applied to the biological domain for protein function prediction.
  • The integration of HMM profiles and secondary structure information provides an advantage in annotation accuracy.
  • The developed program, dataset, and help files are publicly available for further research and application.