The SCOP database in 2020: expanded classification of representative family and superfamily domains of known protein structures

By Antonina Andreeva, Eugene Kulesha, Julian Gough, Alexey G. Murzin. 2019

318 citations recorded by the source corpus.

Abstract The Structural Classification of Proteins (SCOP) database is a classification of protein domains organised according to their evolutionary and structural relationships. We report a major effort to increase the coverage of structural data, aiming to provide classification of almost all domain superfamilies with representatives in the PDB. We have also improved the database schema, provided a new API and modernised the web interface. This is by far the most significant update in coverage since SCOP 1.75 and builds on the advances in schema from the SCOP 2 prototype. The database is accessible from http://scop.mrc-lmb.cam.ac.uk.

Subfields: Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

1. Ben M. Webb
2. Jianzhu Ma
3. Jian Peng
4. Andrej Sali
5. Jinbo Xu
6. G. Lukács
7. Markus M. Geisler
8. T. Hegedűs

In Molecular Biology

1. Ben M. Webb
2. Jinbo Xu
3. Jianzhu Ma
4. Jian Peng
5. Sheng Wang
6. Andrej Sali
7. G. Lukács
8. Markus M. Geisler

Citations in the corpus

• High-resolution de novo structure prediction from primary sequence (2022, background): “75 database with at most 40% sequence identity cutoff ( 32 – 34 ).”
• OpenFold: retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization (2023, unknown): “Multiple structural taxonomies for proteins exist, including the hierarchical classification of protein domain structures (CATH) 34,35 and structural classification of proteins (SCOP) 36 classification systems.”
• RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning (2022, background): “Structural Classification SCOPe (105) and SCOP2 (104,125) Source Organism NCBI Taxonomy (85)”
• Ins and outs of AlphaFold2 transmembrane protein structure predictions (2022, methodology): “Novel structural folds for multi-pass α-helical transmembrane proteins were collected by extensive literature search (match: MprF) and by manual screening of the membrane protein selection of the SCOP database [54] (80 fold families and their subfamilies; http:// scop.”
• Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures (2021, background): “Examples include showing experimental/validation-related data for macromolecular models; displaying various annotations for macromolecular models providing biological context, including SCOP (11), PFAM (12), UniProt (13); the creation of visually interesting, engaging, and interactive educational ma”