Image-centric compression of protein structures improves space savings

Abstract

Motivation: Because of the rapid generation of data, the study of compression algorithms to reduce storage and transmission costs is important to bioinformaticians. Much of the focus has been on sequence data, including both genomes and protein amino acid sequences stored in FASTA files. However, there are few specialized compressors for structural protein data contained in PDB and mmCIF files. Current standard practice is to use an ordinary lossless compressors such as gZip on a sequential list of atomic coordinates, but this approach expends bits on saving an arbitrary ordering of atoms, and it also prevents reordering the atoms for compressibility. In this article, we demonstrate for the first time that image-based compression can significantly improve compression ratios. To this end, we implement a prototype compressor 'PIC', specialized for point clouds of atom coordinates contained in PDB and mmCIF files. PIC maps the 3D data to a 2D 8-bit greyscale image and leverages the well developed PNG image compressor to minimize the size of the resulting image, forming the compressed file. Results: PIC outperforms gZip in terms of compression ratio on proteins over 20,000 atoms in size, with a savings over gZip of up to 37.4% on the proteins compressed. In addition, PIC's compression ratio increases with protein size.

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

“…Various strategies ( Valasatava et al 2017 ) have been proposed to deal with the growth of protein structure databases, including general-purpose compressors like Gzip and data-record-specific encodings like BinaryCIF ( Sehnal et al 2020 ) and MMTF ( Bradley et al 2017 ). PIC ( Staniscia and Yu 2022) transforms 3D coordinates into a lossy 2D image-like format and applies the PNG-image compression algorithm. Specialized formats for molecular trajectories ( Roe and Brooks 2022 ) have also been developed to compress different states of a same molecule.…”

PDC: a highly compact file format to store protein 3D coordinates

“…In addition to lossless compression, some implementations of MMTF also enable lossy compression by retaining only one digit after decimal. On the other hand, the PIC ( 7 ) format only performs lossy compression with a slight loss of precision (usually ∼0.1 Å) by applying the Portable Network Graphics (PNG) compression algorithm for atom positions in the spherical coordinate space. Although PNG is a lossless compression algorithm, the coordinate conversion from Cartesian to spherical space introduces rounding error effects, which makes PIC compression lossy.…”

Efficient protein structure archiving using ProteStAr

“…In the lossy mode, PDC stores approximate coordinate differences between neighboring Cα atoms as well as torsion and side chain angles. Kim et al (2023) evaluated several other approaches to compress protein structures including PULCHRA [8], MMTF [3], PIC [13]. Though, BinaryCIF, Foldcomp, and PDC can be considered as the current state-of-the-art.…”