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Related Concept Videos

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-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...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
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,...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Prediction of protein functional specificity without an alignment.

Andrey Fomenko1, Dmitry Filimonov, Boris Sobolev

  • 1Laboratory for Structure-Function Based Drug Design, Institute of Biomedical Chemistry, Russian Academy of Medical Science, Moscow.

Omics : a Journal of Integrative Biology
|April 6, 2006
PubMed
Summary

We developed a new method using structural Multilevel Neighborhoods of Atom (MNA) descriptors to predict protein functional specificity from amino acid sequences, achieving 0.98 accuracy. This approach outperforms traditional peptide analysis for enzyme classification.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Protein functional specificity is crucial for understanding biological processes.
  • Predicting protein function from amino acid sequences remains a challenge.
  • Traditional methods often represent protein sequences as simple strings of amino acids.

Purpose of the Study:

  • To introduce a novel approach for predicting protein functional specificity.
  • To utilize structural Multilevel Neighborhoods of Atom (MNA) descriptors for sequence representation.
  • To compare the efficacy of MNA descriptors against traditional peptide-based methods.

Main Methods:

  • Developing structural Multilevel Neighborhoods of Atom (MNA) descriptors to represent amino acid sequences.
  • Employing an original Bayesian algorithm for prediction.
  • Analyzing protein sequences as sets of MNA descriptors and as sets of peptides.
  • Conducting a case study on two enzyme nomenclature (EC) subclasses.

Main Results:

  • B-statistics demonstrated sufficient predictive power for both MNA descriptors and peptides.
  • MNA descriptors achieved higher accuracy in predicting enzyme specificity compared to peptides.
  • The choice of MNA descriptor levels allowed for optimization of prediction accuracy.
  • The highest average accuracy achieved was 0.98.

Conclusions:

  • Structural MNA descriptors offer a more accurate method for predicting protein functional specificity than peptide-based representations.
  • The MNA descriptor approach provides flexibility in selecting descriptor levels for enhanced predictive performance.
  • This method shows significant potential for advancing computational approaches in protein function prediction and enzyme classification.