Gene3D: merging structure and function for a Thousand genomes

Lees, Jonathan G.; Yeats, Corin; Redfern, Oliver; Clegg, Andrew B.; Orengo, Christine A.

doi:10.1093/nar/gkp987

Cited by 51 publications

(54 citation statements)

References 26 publications

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“…A more sensitive, but computationally harder, technique is to convert the MSA into a hidden Markov model ( HMM ), which codes insertions or deletions at each position in a profile‐specific way 9, 37. HMM profile‐sequence searches are used in Pfam and Gene3D 38, 39…”

Section: Profile‐sequence Tools Currently Used To Define Domainsmentioning

confidence: 99%

Using HHsearch to tackle proteins of unknown function: A pilot study with PH domains

Fidler¹,

Murphy²,

Courtis³

et al. 2016

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Advances in membrane cell biology are hampered by the relatively high proportion of proteins with no known function. Such proteins are largely or entirely devoid of structurally significant domain annotations. Structural bioinformaticians have developed profile‐profile tools such as HHsearch (online version called HHpred), which can detect remote homologies that are missed by tools used to annotate databases. Here we have applied HHsearch to study a single structural fold in a single model organism as proof of principle. In the entire clan of protein domains sharing the pleckstrin homology domain fold in yeast, systematic application of HHsearch accurately identified known PH‐like domains. It also predicted 16 new domains in 13 yeast proteins many of which are implicated in intracellular traffic. One of these was Vps13p, where we confirmed the functional importance of the predicted PH‐like domain. Even though such predictions require considerable work to be corroborated, they are useful first steps. HHsearch should be applied more widely, particularly across entire proteomes of model organisms, to significantly improve database annotations.

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Section: Profile‐sequence Tools Currently Used To Define Domainsmentioning

confidence: 99%

Using HHsearch to tackle proteins of unknown function: A pilot study with PH domains

Fidler¹,

Murphy²,

Courtis³

et al. 2016

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“…BLAST (Altschul et al 1990), HMMER (Eddy 1998)) and biological databases (i.e. Interproscan (Quevillon et al 2005), GO (Harris et al 2004), Pfam (Finn et al 2008), COGs (Tatusov et al 2000), TIGRFAMs (Haft et al 2003), Gene3D (Lees et al 2010), SUPERFAMILY (Gough and Chothia 2002), PROSITE (Sigrist et al 2010), and PANTHER (Thomas et al 2003).…”

Section: Annotation Of Malic Enzyme Genesmentioning

confidence: 99%

Annotation and analysis of malic enzyme genes encoding for multiple isoforms in the fungus Mucor circinelloides CBS 277.49

et al. 2012

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Based on the newly-released genomic data of Mucor circinelloides CBS 277.49, we have annotated five genes encoding for malic enzyme: all code for proteins that contain conserved domains/motifs for malic acid binding, NAD(+) binding and NAD(P)(+) binding. Phylogenetic analysis for malic enzyme genes showed that genes ID 78524 and 11639 share ~80% amino acid identity and are grouped in cluster 1; genes ID 182779, 186772 and 116127 share ~66% amino acid identity are grouped in cluster 2. Genes ID 78524, 11639 and 166127 produce proteins that are localized in the mitochondrion, while the products from genes 182779 and 186772 are localized in the cytosol. Based on the comparative analysis published previously by Song et al. (Microbiology 147:1507-1515, 2001), we propose that malic enzyme genes ID 78524, 166127, 182779, 186772, 11639, respectively, represent protein isoforms I, II, III/IV, V, and VI.

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“…PANTHER [18] signatures are based on sequences from 48 completed genomes. SUPERFAMILY [19] and Gene3D [20] also use completed genomes as a database source, but they classify the clusters based on the three-dimensional domains from the SCOP [21] and CATH [22] databases.…”

Section: Bioinformatics Tools and Www-based Databasesmentioning

confidence: 99%

Plant protein-coding gene families: emerging bioinformatics approaches

Martínez

2011

Trends in Plant Science

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Protein-coding gene families are sets of similar genes with a shared evolutionary origin and, generally, with similar biological functions. In plants, the size and role of gene families has been only partially addressed. However, suitable bioinformatics tools are being developed to cluster the enormous number of sequences currently available in databases. Specifically, comparative genomic databases promise to become powerful tools for gene family annotation in plant clades. In this review, I evaluate the data retrieved from various gene family databases, the ease with which they can be extracted and how useful the extracted information is.

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Gene3D: merging structure and function for a Thousand genomes

Cited by 51 publications

References 26 publications

Using HHsearch to tackle proteins of unknown function: A pilot study with PH domains

Using HHsearch to tackle proteins of unknown function: A pilot study with PH domains

Annotation and analysis of malic enzyme genes encoding for multiple isoforms in the fungus Mucor circinelloides CBS 277.49

Plant protein-coding gene families: emerging bioinformatics approaches

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