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Foldcomp: a library and format for compressing and indexing large protein structure sets.

Hyunbin Kim1, Milot Mirdita2, Martin Steinegger1,2,3,4

  • 1Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, South Korea.

Bioinformatics (Oxford, England)
|March 24, 2023
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Summary

Foldcomp is a novel lossy compression algorithm that significantly reduces the storage and processing demands of large protein structure datasets. This new method offers superior compression ratios and faster performance for managing structural biology data.

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Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Biology

Background:

  • The rapid advancement of protein structure prediction tools has led to an exponential increase in the number of available protein structures.
  • Managing and processing these massive datasets presents significant computational and storage challenges.

Purpose of the Study:

  • To introduce Foldcomp, a novel lossy compression algorithm and indexing system designed to address the challenges of storing and processing large protein structure datasets.
  • To provide an efficient tool for the management and analysis of extensive protein structure collections.

Main Methods:

  • Foldcomp utilizes a combination of internal and Cartesian coordinates.
  • A bi-directional NeRF-based strategy is employed for enhanced compression.
  • The algorithm incorporates multi-threading and a Python interface for user accessibility.

Main Results:

  • Foldcomp achieves a compression ratio three times greater than existing state-of-the-art methods.
  • The reconstruction error is approximately 0.08 Å, comparable to leading lossy compressors.
  • Foldcomp demonstrates a five-fold increase in speed compared to the next fastest compressor, while maintaining competitive decompression speeds.

Conclusions:

  • Foldcomp offers a highly efficient solution for compressing and managing large-scale protein structure data.
  • Its speed, compression efficiency, and user-friendly interface make it a valuable tool for researchers in structural biology and bioinformatics.
  • The software is available as free open-source, facilitating widespread adoption and analysis of protein structure databases.