Literature DB >> 17034815

Cognate ligand domain mapping for enzymes.

Matthew Bashton1, Irene Nobeli, Janet M Thornton.   

Abstract

Here, we present an automatic assignment of potential cognate ligands to domains of enzymes in the CATH and SCOP protein domain classifications on the basis of structural data available in the wwPDB. This procedure involves two steps; firstly, we assign the binding of particular ligands to particular domains; secondly, we compare the chemical similarity of the PDB ligands to ligands in KEGG in order to assign cognate ligands. We find that use of the Enzyme Commission (EC) numbers is necessary to enable efficient and accurate cognate ligand assignment. The PROCOGNATE database currently has cognate ligand mapping for 3277 (4118) protein structures and 351 (302) superfamilies, as described by the CATH and (SCOP) databases, respectively. We find that just under half of all ligands are only and always bound by a single domain, with 16% bound by more than one domain and the remainder of the ligands showing a variety of binding modes. This finding has implications for domain recombination and the evolution of new protein functions. Domain architecture or context is also found to affect substrate specificity of particular domains, and we discuss example cases. The most popular PDB ligands are all found to be generic components of crystallisation buffers, highlighting the non-cognate ligand problem inherent in the PDB. In contrast, the most popular cognate ligands are all found to be universal cellular currencies of reducing power and energy such as NADH, FADH2 and ATP, respectively, reflecting the fact that the vast majority of enzymatic reactions utilise one of these popular co-factors. These ligands all share a common adenine ribonucleotide moiety, suggesting that many different domain superfamilies have converged to bind this chemical framework.

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Year:  2006        PMID: 17034815     DOI: 10.1016/j.jmb.2006.09.041

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  7 in total

1.  The distribution of ligand-binding pockets around protein-protein interfaces suggests a general mechanism for pocket formation.

Authors:  Mu Gao; Jeffrey Skolnick
Journal:  Proc Natl Acad Sci U S A       Date:  2012-02-21       Impact factor: 11.205

Review 2.  Nothing about protein structure classification makes sense except in the light of evolution.

Authors:  Ruben E Valas; Song Yang; Philip E Bourne
Journal:  Curr Opin Struct Biol       Date:  2009-04-24       Impact factor: 6.809

3.  Characterizing protein domain associations by Small-molecule ligand binding.

Authors:  Qingliang Li; Tiejun Cheng; Yanli Wang; Stephen H Bryant
Journal:  J Proteome Sci Comput Biol       Date:  2012-12-03

4.  The CoFactor database: organic cofactors in enzyme catalysis.

Authors:  Julia D Fischer; Gemma L Holliday; Janet M Thornton
Journal:  Bioinformatics       Date:  2010-08-02       Impact factor: 6.937

Review 5.  Exploiting structural classifications for function prediction: towards a domain grammar for protein function.

Authors:  Benoît H Dessailly; Oliver C Redfern; Alison Cuff; Christine A Orengo
Journal:  Curr Opin Struct Biol       Date:  2009-04-22       Impact factor: 6.809

6.  Knowledge-based annotation of small molecule binding sites in proteins.

Authors:  Ratna R Thangudu; Manoj Tyagi; Benjamin A Shoemaker; Stephen H Bryant; Anna R Panchenko; Thomas Madej
Journal:  BMC Bioinformatics       Date:  2010-07-01       Impact factor: 3.169

7.  PROCOGNATE: a cognate ligand domain mapping for enzymes.

Authors:  Matthew Bashton; Irene Nobeli; Janet M Thornton
Journal:  Nucleic Acids Res       Date:  2007-08-24       Impact factor: 16.971

  7 in total

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