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Related Concept Videos

Protein Organization01:24

Protein Organization

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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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Protein and Protein Structure02:15

Protein and Protein Structure

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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.
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Conservation of Protein Domains Over Different Proteins02:26

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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.
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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...
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Related Experiment Video

Updated: Sep 13, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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Protein structure alignment significance is often exaggerated.

Robert C Edgar, Harutyun Sahakyan

    Biorxiv : the Preprint Server for Biology
    |August 1, 2025
    PubMed
    Summary
    This summary is machine-generated.

    Millions of predicted protein structures require efficient search tools. Our new method accurately estimates statistical significance, correcting overestimations from previous algorithms for reliable protein structure comparison.

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    Area of Science:

    • Computational Biology
    • Structural Bioinformatics
    • Machine Learning Applications

    Background:

    • Machine learning models generate vast numbers of predicted protein structures.
    • Existing structure search algorithms struggle with computational efficiency and accurate statistical significance estimation at scale.
    • Convergent evolution leads to similar structural motifs in unrelated proteins, inflating false positive rates in alignments.

    Purpose of the Study:

    • To develop computationally efficient algorithms for searching large protein structure databases.
    • To provide robust statistical significance estimates for protein structure alignments.
    • To address the overestimation of significance by current methods due to convergent evolution.

    Main Methods:

    • Investigated the tendency of unrelated proteins to evolve similar motifs.
    • Analyzed the performance of popular structure search and alignment algorithms.
    • Developed and validated a novel method for estimating statistical significance (E-values) in large-scale structure searches.

    Main Results:

    • Unrelated proteins exhibit convergent evolution of structural motifs, leading to false positives.
    • Previous methods overestimated statistical significance by up to six orders of magnitude.
    • The novel E-value estimation method is accurate, scalable with database size, and robust to fold diversity.

    Conclusions:

    • Accurate statistical significance estimation is crucial for large-scale protein structure analysis.
    • The new method provides reliable significance values, overcoming limitations of prior approaches.
    • An online service implementing the novel method is available at https://reseek.online.