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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...
Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein.

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Related Experiment Video

Updated: May 27, 2026

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Identification of hub proteins from sequence.

Aswathi Balakrishnan Latha, Achuthsankar Sukumaran Nair, Athmaja Sivasankaran

    Bioinformation
    |November 22, 2011
    PubMed
    Summary

    Predicting protein hubs, key network proteins, is now possible using sequence-based features. This method utilizes physiochemical, thermodynamic, and conformational properties for accurate identification in molecular biology.

    Area of Science:

    • Molecular Biology
    • Bioinformatics
    • Systems Biology

    Background:

    • Identifying protein hubs from primary sequence data presents a significant challenge in molecular biology.
    • Protein hubs are crucial nodes in biological networks, influencing cellular processes.

    Purpose of the Study:

    • To develop and validate a method for predicting protein "hub" status using only amino acid sequence information.
    • To assess the efficacy of sequence-derived features in identifying hub proteins across different species.

    Main Methods:

    • Utilized twenty sequence-based features encompassing physiochemical, thermodynamic, and conformational properties of amino acid residues.
    • Employed Linear Discriminant Analysis (LDA) and a normalized Bayesian approach for prediction modeling.
    • Tested the prediction models on Escherichia coli (E. coli) and Homo sapiens (H. sapiens) datasets.

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    Peptide-based Identification of Functional Motifs and their Binding Partners

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    Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
    14:58

    Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

    Published on: November 12, 2012

    Related Experiment Videos

    Last Updated: May 27, 2026

    An Integrated Approach for Microprotein Identification and Sequence Analysis
    09:37

    An Integrated Approach for Microprotein Identification and Sequence Analysis

    Published on: July 12, 2022

    Peptide-based Identification of Functional Motifs and their Binding Partners
    14:28

    Peptide-based Identification of Functional Motifs and their Binding Partners

    Published on: June 30, 2013

    Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
    14:58

    Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

    Published on: November 12, 2012

    Main Results:

    • Achieved high prediction accuracies for hub proteins using sequence features alone.
    • LDA yielded accuracies of 99.5% for E. coli and 98.6% for H. sapiens.
    • Normalized Bayesian approach resulted in accuracies of 87.8%/89.6% and 90.1%/92.6% for E. coli/H. sapiens, respectively.

    Conclusions:

    • Sequence-based features are effective for predicting protein hub status.
    • The developed methods offer a computationally efficient approach to identify critical proteins in biological networks.
    • This approach facilitates network analysis and understanding of protein function in molecular systems.