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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 Organization01:13

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Conserved Binding Sites01:49

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

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A Memetic Algorithm for 3-D Protein Structure Prediction Problem.

Leonardo Correa, Bruno Borguesan, Camilo Farfan

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |December 29, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel Memetic Algorithm for 3D protein structure prediction, leveraging domain knowledge to efficiently find native-like protein conformations. The approach effectively guides the search, outperforming existing methods in accuracy and folding organization.

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    Area of Science:

    • Computational Biology
    • Bioinformatics
    • Artificial Intelligence

    Background:

    • Protein structure prediction is crucial for understanding biological function.
    • Accurate prediction remains a significant challenge in computational biology.
    • Memetic Algorithms offer a powerful framework for complex optimization problems.

    Purpose of the Study:

    • To develop and evaluate a novel Memetic Algorithm for three-dimensional protein structure prediction.
    • To integrate problem-specific knowledge into the algorithm for enhanced search efficiency.
    • To assess the algorithm's performance against established benchmarks and experimental data.

    Main Methods:

    • A structured population Memetic Algorithm incorporating Simulated Annealing for local search.
    • Custom crossover and mutation operators designed for protein structure data.
    • Utilization of the Protein Data Bank and an Angle Probability List to guide the search space reduction.

    Main Results:

    • The algorithm successfully predicted native-like protein structures for nineteen test sequences.
    • Achieved competitive results in root-mean-square deviation and global distance total score.
    • Demonstrated comparable folding organization to state-of-the-art protein structure prediction methods.

    Conclusions:

    • The proposed Memetic Algorithm is effective for 3D protein structure prediction.
    • Incorporating domain knowledge significantly enhances search efficiency and prediction accuracy.
    • The method shows promise as a valuable tool in computational structural biology.