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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-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...
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...
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...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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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

Protein function prediction with high-throughput data.

Xing-Ming Zhao1, Luonan Chen, Kazuyuki Aihara

  • 1ERATO Aihara Complexity Modelling Project, JST, Tokyo, 151-0064, Japan.

Amino Acids
|April 23, 2008
PubMed
Summary
This summary is machine-generated.

This review details computational methods for protein function prediction using machine learning. It categorizes techniques into supervised, semi-supervised, and unsupervised learning for protein annotation.

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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Protein function prediction is a key challenge in the post-genomic era.
  • High-throughput data offers computational solutions for understanding protein roles.
  • Accurate protein annotation is crucial for biological research.

Purpose of the Study:

  • To provide a comprehensive overview of computational methods for protein function prediction.
  • To focus on machine learning approaches for protein annotation.
  • To present a structured framework for understanding these techniques.

Main Methods:

  • Review of existing computational methods for protein function prediction.
  • Classification of machine learning techniques into supervised, semi-supervised, and unsupervised learning.
  • Analysis of databases and software tools used in protein function prediction.

Main Results:

  • Machine learning offers a powerful computational approach to protein function prediction.
  • Categorizing methods by learning type provides a clear framework for annotation.
  • Numerous databases and tools support computational protein function prediction.

Conclusions:

  • Machine learning is central to modern computational protein function prediction.
  • A structured understanding of ML techniques aids in selecting appropriate annotation tools.
  • The review serves as a guide to current methodologies and resources in the field.