History of the enzyme nomenclature system

Tipton, Keith F.; Boyce, Sinéad

doi:10.1093/bioinformatics/16.1.34

Cited by 118 publications

(65 citation statements)

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“…The proposal of GO is to characterize the gene product by ontologies rather than by function nomenclature (molecular name) as it is done in this work (Chitale and Kihara, 2011;The Gene Ontology Consortium, 2013). The function nomenclature is the role of the protein in the organism in which it is expressed (Tripton and Boyce, 2000) and it is present in the "definition" field of the GenBank format file (file format for gene sequences) or GenPept (format file for protein sequences) in NCBI (U.S. National Library of Medicine, 2014). The contingency table methodology used in other assessments needs to reduce the classifications into two classification categories and only allows the assessment of one program and one dataset at each time (Thomas et al, 2003a;Prati et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

Quantitative assessment of protein function prediction programs

Rodrigues¹,

Steffens²,

Raittz³

et al. 2015

Genet. Mol. Res.

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ABSTRACT. Fast prediction of protein function is essential for highthroughput sequencing analysis. Bioinformatic resources provide cheaper and faster techniques for function prediction and have helped to accelerate the process of protein sequence characterization. In this study, we assessed protein function prediction programs that accept amino acid sequences as input. We analyzed the classification, equality, and similarity between programs, and, additionally, compared program performance. The following programs were selected for our assessment: Blast2GO, InterProScan, PANTHER, Pfam, and ScanProsite. This selection was based on the high number of citations (over 500), fully automatic analysis, and the possibility of returning a single best classification per sequence. We tested these programs using 12 gold standard datasets from four different sources. The gold standard classification of the databases was based on expert analysis, the Protein Data Bank, or the Structure-Function Linkage Database. We found that the miss rate among the programs is globally over 50%. Furthermore, we observed little overlap in the correct predictions from each program. Therefore, a combination of multiple types of sources 17555-17566 (2015) and methods, including experimental data, protein-protein interaction, and data mining, may be the best way to generate more reliable predictions and decrease the miss rate.

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Section: Discussionmentioning

confidence: 99%

Quantitative assessment of protein function prediction programs

Rodrigues¹,

Steffens²,

Raittz³

et al. 2015

Genet. Mol. Res.

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“…EC-(Enzyme Commission) numbers thus consist of 4 numbers, where at each level, the number denotes to which category the enzyme belongs. A review of the development of the enzyme nomenclature and classification can be found in Tipton and Boyce [14]. For future reference, we will make a few definitions.…”

Section: Estimation Of Correctness Using Enzyme Classificationmentioning

confidence: 99%

“…PPARD only has one original article 12 . According to SCI there are 198 13 articles that refer to this article, but we could only obtain reference lists for 154 14 of them. In these 154 reference lists, we identified 187 unique original articles and each of them represents one gene symbol that has been co-referred with the original article of PPARD.…”

Section: Assessment Of Completeness Using Sci Citation Datamentioning

confidence: 99%

Methods for Large-Scale Mining of Networks of Human Genes

Jenssen

Öberg

Andersson

et al. 2001

Proceedings of the 2001 SIAM International Conference on Data Mining

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In molecular biology there is much interest in various types of relationships between genes. Due to the complexity and rapid development of this field, much of this knowledge exists only in free-text form. A database of relationships between genes may allow background knowledge to be used in computerised analyses. As far as we know, no comprehensive manually cured database of this kind exists, and constructing and maintaining such a database manually would be very labour-intensive. Efficient automated methods for extraction and structuring of relationships between genes from free-text would be valuable. A database named PubGene has previously been created and it contains a comprehensive network of human genes created by automated extraction of co-occurrence of gene terms in over 10 million MEDLINE records. Co-occurring genes were linked together under the hypothesis that two genes will co-occur only if they have some biological relationship. In this paper, we show that for the subset of human genes encoding enzymes, pairs of co-occurring enzyme genes are significantly more closely related biologically than when these genes are compared randomly. Manual inspection, however, shows that some of the links in PubGene are not correct and it also indicates how the noise can be reduced. We propose a complementary method for automated extraction of relationships between genes by use of information from the Science Citation Index (SCI) database. We relate two genes if they have been co-referred, that is, having reference articles being co-cited in a third article. The alternative approach confirms relationships found in PubGene, and it also finds other relevant relationships.

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“…A timeline of historic events in biocatalysis and biotechnology is outlined in Table 1. [18][19][20] Reviews and Accounts Novel methodologies for discovering industrial enzymes based on genomic sequencing and phage display (discussed further in Section 1.3), 21,22 as well as highly effective optimisation tools based on chemical, physical and molecular biology approaches, 23 have improved the access to biocatalysts, increased their stability, and radically broadened their specificity. …”

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confidence: 99%

Recent trends in whole cell and isolated enzymes in enantioselective synthesis

Milner¹,

Maguire²

2012

Arkivoc

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Modern synthetic organic chemistry has experienced an enormous growth in biocatalytic methodologies; enzymatic transformations and whole cell bioconversions have become generally accepted synthetic tools for asymmetric synthesis. This review details an overview of the latest achievements in biocatalytic methodologies for the synthesis of enantiopure compounds with a particular focus on chemoenzymatic synthesis in non-aqueous media, immobilisation technology and dynamic kinetic resolution. Furthermore, recent advances in ketoreductase technology and their applications are also presented.Keywords: Biocatalysis, kinetic and dynamic kinetic resolution, Baker's yeast, ketoreductases General IntroductionAsymmetric synthesis is the preferential formation of one stereoisomer of a chiral target compound to another; when scientists at GlaxoSmithKline, AstraZeneca and Pfizer 1 examined 128 syntheses from their companies, they found as many as half of the drug compounds made by their process research and development groups are not only chiral but also contain an average of two chiral centres each. 2In 2006 just 25 % were derived from the chiral pool and over 50 % employed chiral technologies. 1In order to meet regulatory requirements enantiomeric purities of 99.5 % were deemed necessary by the FDA. 3 This is one of the biggest challenges which face chemists today, primarily due to the recognition of the fact that different enantiomers of the same compound can interact differently in biological systems. As a consequence, the production of single enantiomers instead of racemic mixtures has become an important process in the pharmaceutical and agrochemical industry. Several routes can lead to the desired enantiomer including transition metal-, [4][5][6] organo-5,7-10 and bio-catalysis [11][12][13][14][15] and these have been thoroughly reviewed in the literature. 16,17 2. Biocatalysis IntroductionBiocatalysis involves the use of enzymes or whole cells (containing the desired enzyme or enzyme system) as catalysts for chemical reactions. A timeline of historic events in biocatalysis and biotechnology is outlined in Table 1. [18][19][20] Reviews and Accounts Novel methodologies for discovering industrial enzymes based on genomic sequencing and phage display (discussed further in Section 1.3), 21,22 as well as highly effective optimisation tools based on chemical, physical and molecular biology approaches, 23 have improved the access to biocatalysts, increased their stability, and radically broadened their specificity. 24This greater availability of catalysts with superior qualities including the use of new bioengineering tools contributed significantly to the development of new industrial processes. Biocatalytic methodologies for organic synthesis were outlined by Woodley et al. in three categories: established, emerging and expanding chemistries as depicted in Figure 1. 25 Enzyme classesBy the late 1950s it had become evident that the nomenclature of enzymes without any guiding authority, in a period when the...

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History of the enzyme nomenclature system

Cited by 118 publications

References 1 publication

Quantitative assessment of protein function prediction programs

Quantitative assessment of protein function prediction programs

Methods for Large-Scale Mining of Networks of Human Genes

Recent trends in whole cell and isolated enzymes in enantioselective synthesis

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