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Related Concept Videos

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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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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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.
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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...
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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.
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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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Artificial Intelligence Learns Protein Prediction.

Michael Heinzinger1, Burkhard Rost2,3,4,5

  • 1Technical University of Munich (TUM) School of School of Computation, Information and Technology (CIT), Bioinformatics and Computational Biology - i12, 85748 Garching/Munich, Germany mheinzinger@rostlab.org.

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Summary
This summary is machine-generated.

Artificial intelligence (AI) is revolutionizing biology. Advanced AI tools like AlphaFold2 and protein language models (pLMs) are accelerating biological research and enabling powerful new protein design capabilities.

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Area of Science:

  • Computational Biology
  • Artificial Intelligence
  • Molecular Biology

Background:

  • Recent advancements in artificial intelligence (AI) have led to breakthroughs in various scientific fields.
  • Computational biology is rapidly evolving, mirroring AI's progress with tools like AlphaFold2 for protein structure prediction.

Purpose of the Study:

  • To highlight the transformative impact of AI on molecular and medical biology.
  • To emphasize the potential of AI in advancing protein design.

Main Methods:

  • Leveraging large-scale protein sequence databases.
  • Utilizing deep learning techniques for pattern recognition in protein data.
  • Development of protein language models (pLMs).

Main Results:

  • Protein language models (pLMs) now surpass traditional methods relying on expertise and multiple sequence alignments.
  • AI tools are significantly increasing experimental data and accelerating the research cycle.
  • AI is paving the way for enhanced protein design capabilities.

Conclusions:

  • AI is fundamentally changing molecular and medical biology.
  • The integration of AI is crucial for future biological discoveries and applications.
  • AI-driven protein design represents a major leap forward in the field.