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MDCompress: better, faster compression of molecular dynamics simulation trajectories
Open accessPreprint — published as 10.1093/bioinformatics/btag176
Abstract
Motivation: Molecular dynamics (MD) simulations model the physical movements of atoms in biomolecular systems over time, providing atomic-resolution insight into conformational changes, binding events, and dynamic behaviors that cannot be captured by static structures alone. As such, MD simulations are playing an increasingly important role in understanding the functional roles and molecular interactions of proteins. However, trajectories from these simulations can be extremely large, often reaching tens of gigabytes for a single simulation of modest duration. This creates substantial challenges for storage and data transfer, motivating efficient compression strategies. Furthermore, many downstream analyses require extraction of only a subset of frames or specific atoms from the full trajectory, so an ideal compression format should support rapid random-access decompression of such samplings without requiring full file decompression. Results: Here, we introduce MDCompress, a new trajectory compression format and accompanying software implementation that meets these goals. MDCompress produces compressed trajectory files that are 15–37% smaller than those generated by the widely-used XTC format, while achieving faster compression and decompression speeds through efficient multithreading. Availability and Implementation: The MDCompress software and library are released under an open license (BSD-3) and may be downloaded at https://github.com/refresh-bio/mdcompress Contact: twheeler@arizona.edu , sebastian.deorowicz@polsl.pl Supplementary information: Supplementary data are available online.
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Metadata
- Authors
- Kokot, M., Roy, A., Wheeler, T. J., & Deorowicz, S.
- Affiliations
- Silesian University of Technology (PL)
- University of Montana (US)
- University of Arizona (US)
- Corresponding author
- Wheeler, Travis J
- Deorowicz, Sebastian
- Venue
- Bioinformatics
- Publisher
- openRxiv
- Published
- 2025-12-22
- Volume
- 42
- Issue
- 4
- ISSN
- 1367-4803 (ISSN-L)
- OpenAlex
- W7154076621
- Cited by
- 0
- References
- 21
- FWCI
- 0.00
- 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 (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- Funders
- National Science Centre, Poland (DEC-2022/45/B/ST6/03032)
- University of Arizona Research (Innovation & Impact (RII) through BIO5 and IT4IR TRIF Funds)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
- Keywords
- molecular dynamics trajectories, trajectory compression, multithreading, data storage and transfer, biomolecular simulation, protein dynamics
- MeSH terms
- Compression Algorithms, Proteins, Software, Data Compression, Molecular Dynamics Simulation
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