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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 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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Overview
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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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Tail-anchored, or TA, proteins are estimated to make up to 3-5% of membrane proteins found in the eukaryotic cell. Such proteins have a single transmembrane domain located approximately 30 amino acid residues upstream from the C-terminal end. As a result, the signal recognition particle (SRP) cannot guide a TA protein to the ER membrane for cotranslational insertion. Hence, they are integrated into the ER membrane post-translationally using their C-terminal end as the anchor. TA proteins...
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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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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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Efficient protein structure archiving using ProteStAr.

Sebastian Deorowicz1, Adam Gudyś1

  • 1Department of Algorithmics and Software, Silesian University of Technology, Akademicka 16, Gliwice, PL-44100, Poland.

Bioinformatics (Oxford, England)
|July 10, 2024
PubMed
Summary
This summary is machine-generated.

ProteStAr efficiently compresses large protein structure files (CIF/PDB) using a novel prediction method. This tool significantly reduces data size for large-scale analyses, outperforming existing methods.

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Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational chemistry

Background:

  • DeepMind's AlphaFold 2 generates millions of protein structures in CIF/PDB formats.
  • Large datasets (tens of terabytes) hinder large-scale structural analyses.
  • Existing compression methods are insufficient for predicted protein structure data.

Purpose of the Study:

  • Introduce ProteStAr, a specialized compressor for protein structure files (CIF/PDB) and associated PAE files.
  • Develop a novel compression approach for efficient encoding of atomic coordinates.
  • Enable faster and more accessible large-scale analysis of predicted protein structures.

Main Methods:

  • Developed a novel algorithm for predicting atom coordinates based on previously analyzed atoms.
  • Implemented both lossless and lossy compression modes with controlled error.
  • Optimized the algorithm for multicore CPUs, achieving speeds of approximately 1 GB/s.
  • Provided Python and C++ APIs for enhanced usability.

Main Results:

  • ProteStAr achieves superior compression ratios compared to BinaryCIF, Foldcomp, and PDC at comparable reconstruction accuracy.
  • The method efficiently encodes atomic coordinates, the largest data component in structure files.
  • High-speed compression and decompression (approx. 1 GB/s) leverage multicore architectures.
  • Lossy mode allows controlled error for further data reduction.

Conclusions:

  • ProteStAr offers a significant improvement in compressing large protein structure datasets.
  • The tool facilitates large-scale structural bioinformatics analyses by reducing data storage and transfer requirements.
  • Its speed, efficiency, and accessibility (via APIs) make it valuable for researchers.