/symmetry-benchmark

Benchmarks for testing the symmetry package

Primary LanguagePython

symmetry-benchmark

This project was designed to benchmark results of CE-Symm, accompanying symmetry. Please see that project for more general information.

Users may be interested in this project to:

  • Benchmark alternative data sets using CE-Symm.
  • Reproduce the benchmarks in the CE-Symm paper.
  • Benchmark protein symmetry-detection algorithms other than CE-Symm.

CE-Symm Benchmark (Myers-Turnbull 2014)

Myers-Turnbull, D., Bliven, S. E., Rose, P. W., Aziz, Z. K., Youkharibache, P., Bourne, P. E., & Prlić, A. (2014). Systematic Detection of Internal Symmetry in Proteins Using CE-Symm. Journal of Molecular Biology, 426(11), 2255–2268.

The CE-Symm algorithm was originally benchmarked on a novel manually curated set of 1007 proteins. These are annoted with various types of structural repeats, primarily internal symmetry.

The Myers-Turnbull benchmark is contained in file domain_symm_benchmark.tsv. The original file can be accessed from the symmetry-benchmark-1.0.0 tag, and can be used to exactly duplicate the results from the paper (together with the CE-Symm 1.0.0 Release). Later releases reflect changes in the PDB (e.g. obsolete entries) or the discovery of mistakes in the manual curation (e.g. overlooked translational repeats).

Each line of the file consists of a SCOPe domain identifier (v. 2.01) and an annotation of the symmetry. Abbreviations used:

  • C1 Asymmetric
  • C[x] Rotational symmetry, order x. The repeats should be arranged in a closed ring, with a reasonably consistent orientation between repeats. Specification of the superposition requires one axis, with a 2pi/x rotation.
  • D[x] Dihedral symmetry, with an x-fold major axis and 2x repeats. An additional x two-fold rotation axes are arranged perpendicular to the major axis. Two axes are required to specify the superposition.
  • H[x] Helical symmetry with x repeats per revolution. Helices with integer x arise commonly in crystalline environments. The superposition requires an axis for the 2pi/x rotation and a translation distance along this axis.
  • NIH Non-integer helical repeats. These give cases with a non-integer number of subunits per rotation. Superposition can involve an arbitrary transformation between subunits.
  • SH Superhelical repeats. Used for cases where multiple levels of helices are detectable. This is analogous to supercoiling in leucine zippers or DNA, but with a fundamental repeat of secondary structure elements rather than individual residues. The full superposition cannot be simply represented, as the orientation between adjacent repeats depends on their position in the higher-level helices. However, for some applications it may be sufficient to specify the axis of the top-level helix.
  • R[x] Translational repeats without higher structure or symmetry, x repeats.

Classification guidelines

Many of the cases in the benchmark are difficult to classify or fall near the border of two categories. The following guidelines were used for difficult cases:

  • Within repeats, the order of aligned elements should be the same. Don't consider cases where a strand or helix would superimpose well but with opposite direction (as sometimes occurs near the axis of symmetry between repeats).
  • Clear cases of domain swapping are allowed, and both swapped and unswapped structures should be considered for classification.
  • Ideally, the orientation between repeats should be consistent among all repeats. However, if repeats are still identifiable then count them even in the presence of large distortions. Controversial cases are tagged #distortion in the issues.
  • The majority of the domain should be convered by repeats. The exact size and complexity of insertions should be evaluated on a case-by-case basis. Controversial cases with poor coverage are tagged #partial in the issues.
  • Alpha helical bundles are particularly tricky, since they tend to superimpose well despite kinks and inconsistencies. Most bundles were marked as symmetric if they could be aligned with consistent topology.

Changelog

  • 1.0.0 Published benchmark (1007 structures)

Other Benchmarks

Guerler folds

Guerler, A., Wang, C., & Knapp, E. W. (2009). Symmetric structures in the universe of protein folds. Journal of Chemical Information and Modeling, 49(9), 2147–2151.

The GANGSTA+ algorithm for detecting internal symmetry was run on ASTRAL40 (SCOP v. 1.73) and identified a number of families with significant internal symmetry. Both SymD and CE-Symm also used the dataset, making it a useful tool for comparing algorithms.

Kim et al. provide a list of SCOP domains for each symmetric fold in their Supplemental Material 3:

Kim, C., Basner, J., & Lee, B. (2010). Detecting internally symmetric protein structures. BMC Bioinformatics, 11, 303.

This data has been reformatted into a more machine-readable format in the Guerler_folds/ directory. We were unable to reconcile some differences in the number of domains with those given in Kim Table 2. The data here can be used to reproduce the CE-Symm results from Myers-Turnbull Table 1, but they may not reproduce exactly the previously reported SymD and GANGSTA+ results.

Format:

Guerler_folds/expected_groups.tsv contains a list of SCOP folds and families, annotated with the expected type of symmetry.

Guerler_folds/*.list contains a list of SCOP domains belonging to the fold given in the filename.

Fisher benchmark

Fischer, D., Elofsson, A., Rice, D., & Eisenberg, D. (1996). Assessing the performance of fold recognition methods by means of a comprehensive benchmark. Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing, 300–318.

The Fischer benchmark consists of 68 pairs of proteins from related folds. While not directly related to symmetry, the list of proteins is provided here in machine-readable format for benchmarking structural comparison algorithms.