MMTF—An efficient file format for the transmission, visualization, and analysis of macromolecular structures

By Anthony R. Bradley, Alexander S. Rose, Antonín Pavelka, Yana Valasatava, Jose M. Duarte, Andreas Prlic, Peter W. Rose. 2017

48 citations recorded by the source corpus.

Recent advances in experimental techniques have led to a rapid growth in complexity, size, and number of macromolecular structures that are made available through the Protein Data Bank. This creates a challenge for macromolecular visualization and analysis. Macromolecular structure files, such as PDB or PDBx/mmCIF files can be slow to transfer, parse, and hard to incorporate into third-party software tools. Here, we present a new binary and compressed data representation, the MacroMolecular Transmission Format, MMTF, as well as software implementations in several languages that have been developed around it, which address these issues. We describe the new format and its APIs and demonstrate that it is several times faster to parse, and about a quarter of the file size of the current standard format, PDBx/mmCIF. As a consequence of the new data representation, it is now possible to visualize structures with millions of atoms in a web browser, keep the whole PDB archive in memory or parse it within few minutes on average computers, which opens up a new way of thinking how to implement efficient algorithms in structural bioinformatics. The PDB archive is available in MMTF file format through web services and data are updated on a weekly basis.

Subfields: Artificial Intelligence, Materials Chemistry, Molecular Biology

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In Artificial Intelligence

Alexander S. Rose

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Citations in the corpus

RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy (2018, methodology): “NGL Viewer uses an internally developed binary compressed format (Macromolecular Transmission Format) that considerably reduces network transfer and parsing time requirements (42).”
Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures (2021, unknown): “The project builds on the code and knowledge the authors gained from developing web-based molecular viewers, analysis tools, and compressed file formats, including the LiteMol Suite (14), the NGL Viewer (15,16), PatternQuery (17), MMTF (18,19) and BinaryCIF (20).”
The Bio3D packages for structural bioinformatics (2020, unknown): “Other potential future developments include connections to sequence databases and servers for directly mapping structural dynamics to next-generation sequencing data, more efficient memory management for analyses of especially large systems and long MD trajectories, continued improvement of I/O incl”