SCOP: Structural Classification of Proteins and ASTRAL

Structural Classification of Proteins and ASTRAL release 1.75B (January 2013)

Welcome to the new SCOP+Astral website!

This is the second in a series of planned stable SCOP+Astral releases based on the SCOP legacy version, 1.75. They will provide automated classification of many new structures while work on a major reclassification, SCOP 2.0, is in progress. This website now provides all data previously found in the SCOP and Astral databases. For prior releases of SCOP and Astral, click on the Stats & History tab above.

The SCOP authors are Alexey G. Murzin, John-Marc Chandonia, Antonina Andreeva, Dave Howorth, Loredana Lo Conte, Bartlett G. Ailey, Steven E. Brenner, Tim J. P. Hubbard, and Cyrus Chothia.

The ASTRAL authors are John-Marc Chandonia, Naomi K. Fox, Degui Zhi, Gary Hon, Loredana Lo Conte, Nigel Walker, Patrice Koehl, Michael Levitt, and Steven E. Brenner.

Postdoc Wanted! Want to help us design and build the next generation of SCOP and ASTRAL? Get more details and apply here.

Synopsis and News:

Nearly all proteins have structural similarities with other proteins and, in some of these cases, share a common evolutionary origin. The SCOP database, created by manual inspection and abetted by a battery of automated methods, aims to provide a detailed and comprehensive description of the structural and evolutionary relationships between all proteins whose structure is known. As such, it provides a broad survey of all known protein folds, detailed information about the close relatives of any particular protein, and a framework for future research and classification.

We are developing SCOP 2.0, a major reclassification of the database. The tree-like hierarchy of older versions of SCOP will be replaced by a complex network of hierarchical and non-hierarchical relationships represented by a directed acyclic graph. This network will allow us to represent the structural and most likely evolutionary relationships between proteins in more precise detail. This work is primarily being carried out by the Cambridge team in the UK (Antonina Andreeva, David Howorth and Alexey G. Murzin).

The Astral compendium provides databases and tools useful for analyzing protein structures and their sequences. It is partially derived from, and augments SCOP. Most of the resources provided here depend upon the coordinate files maintained and distributed by the Protein Data Bank.

In this release, we have continued to take a very conservative approach to using automation to classify new structures: only full-length chains that could be confidently matched to existing, manually curated SCOP domains in the first 7 SCOP classes were added. We are continuing to benchmark our automated classification methods against prior versions of SCOP, to be sure the results of automation are completely consistent with manual curation. In addition, we corrected several bugs in this release—click on the Stats & History tab for details. This work is currently carried out in Berkeley, USA by the SCOP and ASTRAL authors John-Marc Chandonia, Naomi K. Fox, and Steven E. Brenner, with a contribution from the Cambridge team.

Starting with this release, we will produce periodic updates (approximately monthly) that include confident automated classifications of newly released protein structures. The updates will include the latest structures, while less frequent stable releases will include bug fixes and will continue to provide a foundation for benchmarks. Parseable files for both stable releases and periodic updates will be made available under the Downloads tab.

This release is also the first to include a web interface that provides integrated access to data from prior versions of SCOP and Astral. To access prior releases, click on the Stats & History tab above.

Other improvements in the 1.75-based series include an updated web interface (which is still being developed and improved), and a SQL back end (click the Downloads tab to obtain a copy).

Funding:

This work is supported by the National Institutes of Health (R01-GM073109). Antonina Andreeva, David Howorth and Alexey G. Murzin are also supported by the Medical Research Council (MC_US_A025_0067). John-Marc Chandonia and Naomi K. Fox are also supported by the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.