Towards an efficient compression of 3D coordinates of macromolecular structures

• Published in: PloS one Vol. 12; no. 3; p. e0174846
• Main Authors: Valasatava, Yana, Bradley, Anthony R, Rose, Alexander S, Duarte, Jose M, Prlić, Andreas, Rose, Peter W
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 31.03.2017; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Arches; Archives & records; Assemblies; Atomic structure; Bandwidth; Biochemistry; Bioinformatics; Biology; Biology and Life Sciences; Complexity; Compression; Compression ratio; Computation; Computer and Information Sciences; Computer applications; Computer programs; Construction; Crystallography; Data analysis; Data Compression; Data processing; Data transmission; Databases, Protein; Datasets; Decomposition; Decompression; Deposition; Dynamics; Electron microscopy; HIV; Human immunodeficiency virus; Information management; Internet; Laboratories; Macromolecules; Magnetic Resonance Spectroscopy; Mathematical analysis; Mathematical models; Mathematics; Methods; Models, Theoretical; Molecular Structure; Physical Sciences; Polymers; Polynomials; Protein structure; Protein Structure, Secondary; Protein Structure, Tertiary; Proteins; Quality control; RcsB protein; Reduction; Redundancy; Research and Analysis Methods; Software; Software upgrading; Strings; Structural members; Supercomputers; Supports; Symmetry; Three dimensional displays; Trajectories; Viruses; Visualization; United States; La Jolla California; United States > US; California
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0174846

The size and complexity of 3D macromolecular structures available in the Protein Data Bank is constantly growing. Current tools and file formats have reached limits of scalability. New compression approaches are required to support the visualization of large molecular complexes and enable new and scalable means for data analysis. We evaluated a series of compression techniques for coordinates of 3D macromolecular structures and identified the best performing approaches. By balancing compression efficiency in terms of the decompression speed and compression ratio, and code complexity, our results provide the foundation for a novel standard to represent macromolecular coordinates in a compact and useful file format.