The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data

By Craig T. Porter, G. Bartlett, Janet M. Thornton. Nucleic Acids Res., 2004

626 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/9003c585b77ef75a9007e249ac7ec40c31fd1077

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. Jianyi Yang
2. Yang Zhang
3. Ambrish Roy
4. Michael J.E. Sternberg
5. Jens Meiler
6. Roman A. Laskowski
7. Janet M. Thornton
8. Lawrence A. Kelley

In Molecular Biology

1. Yang Zhang
2. Jianyi Yang
3. Ambrish Roy
4. Michael J.E. Sternberg
5. Lawrence A. Kelley
6. Robin Pearce
7. Jens Meiler
8. Janet M. Thornton

In Spectroscopy

1. Jianyi Yang
2. Yang Zhang
3. Ambrish Roy
4. Roman A. Laskowski
5. James D. Watson
6. John A. Capra
7. Mona Singh
8. Morten Nielsen

Citations in the corpus

• Comprehensive structural classification of ligand-binding motifs in proteins. (2008, background): “So far, such structural motifs have been determined either manually (Porter et al., 2004) or automatically (Wangikar et al.”
• The Proteomics Protocols Handbook (2005, background): “However, for the case of plants, there is also the issue of metabolites from secondary metabolism interfering with the separation process (84,85).”
• Predicting functionally important residues from sequence conservation (2007, background): “secondary structure and solvent accessibility), used along with conservation, can be used within machine-learning methods to identify particular types of functional residues (Bordner and Abagyan, 2005; Petrova and Wu, 2006 ).”
• SuSPect: Enhanced Prediction of Single Amino Acid Variant (SAV) Phenotype Using Network Features (2014, methodology): “Catalytic sites from the Catalytic Site Atlas [40] and protein interface residues from PISite [41] and ProtInDBc were obtained for PDB structures.”
• ProFunc: a server for predicting protein function from 3D structure (2005, methodology): “The template database was originally called PROCAT and searched using a program called TESS (22), but has now been superseded by the Catalytic Site Atlas (23) and is searched by Jess (21).”
• Computational Methods in Drug Discovery (2014, methodology): “Catalytic Site Atlas contains annotated descriptors of enzyme active site residues as well as equivalent sites in related proteins found by sequence alignment.”
• Predicting protein function from sequence and structure (2007, neutral): “uk/thornton-srv/databases/CSA/">Catalytic Site Atlas”
• MOLEonline: a web-based tool for analyzing channels, tunnels and pores (2018 update) (2018, methodology): “Catalytic site amino acids, uploaded automatically from the CSA database, can also be used as the starting point (23).”
• MOLE 2.0: advanced approach for analysis of biomacromolecular channels (2013, methodology): “uk/ thornton-srv/databases/CSA/) [49] to be used as well as automatic identification of start points in a given structure.”
• FireDB: a compendium of biological and pharmacologically relevant ligands (2013, methodology): “FireDB brings together ligands crystallized in PDB structures, the residues in contact with those ligands, and the catalytic sites annotated by hand in the Catalytic Site Atlas (14).”
• BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions (2012, positive): “For each protein chain (called receptor), the information (if any) to be collected includes the following: (i) ligand-binding affinity from manual survey of the original literature and the existing databases of Binding MOAD (5), PDBbind (4) and BindingDB (6); (ii) catalytic site residues mapped from”
• Networks of High Mutual Information Define the Structural Proximity of Catalytic Sites: Implications for Catalytic Residue Identification (2010, methodology): “The dataset was constructed based on the CSA database (version 2.2.11, released August 2009) [32].”
• COFACTOR: an accurate comparative algorithm for structure-based protein function annotation (2012, methodology): “However, the data of GO and EC classifications are collected from other secondary resources (19,29,30), the updates of which are therefore not as regular and rely on the update of these resources.”
• Predicting protein function from sequence and structural data. (2005, background): “The prime example of the former are the templates derived from the Catalytic Site Atlas (CSA) [30].”