Foldcomp: a library and format for compressing and indexing large protein structure sets
Open accessPublished version of a preprint
Abstract
Summary: Highly accurate protein structure predictors have generated hundreds of millions of protein structures; these pose a challenge in terms of storage and processing. Here, we present Foldcomp, a novel lossy structure compression algorithm, and indexing system to address this challenge. By using a combination of internal and Cartesian coordinates and a bi-directional NeRF-based strategy, Foldcomp improves the compression ratio by a factor of three compared to the next best method. Its reconstruction error of 0.08 Å is comparable to the best lossy compressor. It is five times faster than the next fastest compressor and competes with the fastest decompressors. With its multi-threading implementation and a Python interface that allows for easy database downloads and efficient querying of protein structures by accession, Foldcomp is a powerful tool for managing and analysing large collections of protein structures. Availability and implementation: Foldcomp is a free open-source software (GPLv3) and available for Linux, macOS, and Windows at https://foldcomp.foldseek.com. Foldcomp provides the AlphaFold Swiss-Prot (2.9GB), TrEMBL (1.1TB), and ESMatlas HQ (114GB) database ready-for-download.
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Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Self-citationVaradi, M., Anyango, S., Deshpande, M., Nair, S., Natassia, C., Yordanova, G., Yuan, D., Stroe, O., Wood, G., Laydon, A., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1061 · Cited by 7,850 · see citing works
Evolutionary-scale prediction of atomic level protein structure with a language model
Lin, Z., Akin, H., Rao, R., Hie, B., Zhu, Z., Lu, W., Smetanin, N., Verkuil, R., Kabeli, O., Shmueli, Y., et al. (2022) · doi:10.1101/2022.07.20.500902 · Cited by 5,523 · see citing works
Fast and accurate protein structure search with Foldseek
van Kempen, M., Kim, S. S., Tumescheit, C., Mirdita, M., Lee, J., Gilchrist, C. L. M., Söding, J., & Steinegger, M. (2022) · doi:10.1101/2022.02.07.479398 · Cited by 2,598 · see citing works
Self-citationFast and accurate protein structure search with Foldseek
van Kempen, M., Kim, S. S., Tumescheit, C., Mirdita, M., Lee, J., Gilchrist, C. L. M., Söding, J., & Steinegger, M. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01773-0 · Cited by 2,596 · see citing works
Self-citationPipkins, H. R., Bradshaw, J. L., Keller, L. E., Swiatlo, E., & McDaniel, L. S. (2017) · PLOS ONE · doi:10.1371/journal.pone.0179159 · Cited by 1,338 · see citing works
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Fast and accurate protein structure search with Foldseek
van Kempen, M., Kim, S. S., Tumescheit, C., Mirdita, M., Lee, J., Gilchrist, C. L. M., Söding, J., & Steinegger, M. (2022) · doi:10.1101/2022.02.07.479398 · Cited by 2,598 · see citing works
Self-citationFast and accurate protein structure search with Foldseek
van Kempen, M., Kim, S. S., Tumescheit, C., Mirdita, M., Lee, J., Gilchrist, C. L. M., Söding, J., & Steinegger, M. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01773-0 · Cited by 2,596 · see citing works
Self-citationClustering predicted structures at the scale of the known protein universe
Barrio-Hernandez, I., Yeo, J., Jänes, J., Mirdita, M., Gilchrist, C. L. M., Wein, T., Varadi, M., Velankar, S., Beltrao, P., & Steinegger, M. (2023) · Nature · doi:10.1038/s41586-023-06510-w · Cited by 362 · see citing works
Self-citationStructural motif search across the protein universe with Folddisco
Kim, H., Kim, R. S., Mirdita, M., Yoon, J., & Steinegger, M. (2026) · Nature Biotechnology · doi:10.1038/s41587-026-03162-9 · Cited by 10 · see citing works
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- Authors
- Kim, H., Mirdita, M., & Steinegger, M.
- Affiliations
- Seoul National University (KR)
- Corresponding author
- Mirdita, Milot
- Steinegger, Martin
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2023-03-24
- Volume
- 39
- Issue
- 4
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC10085514
- OpenAlex
- W4360807834
- Cited by
- 29
- References
- 6
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 8 · 2023: 6
- FWCI
- 2.58
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Funders
- National Research Foundation of Korea (2019R1A6A1A10073437, 2020M3A9G7103933, 2021R1C1C102065, 2021M3A9I4021220)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
- Keywords
- lossy compression, neural radiance fields, protein structure database, Cartesian coordinates, protein structure retrieval
- MeSH terms
- Algorithms, Proteins, Software, Gene Library, Data Compression
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