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izvor podataka: crosbi

Databases of the Thiotemplate Modular Systems (CSDB) and their in silico recombinants (r-CSDB) (CROSBI ID 199945)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Diminić, Janko ; Žučko, Jurica ; Trninić Ruzić, Ida ; Gačeša, Ranko ; Hranueli, Daslav ; Long, Paul F. ; Cullum, John ; Starčević, Antonio Databases of the Thiotemplate Modular Systems (CSDB) and their in silico recombinants (r-CSDB) // Journal of industrial microbiology & biotechnology, 40 (2013), 6; 653-659. doi: 10.1007/s10295-013-1252-z

Podaci o odgovornosti

Diminić, Janko ; Žučko, Jurica ; Trninić Ruzić, Ida ; Gačeša, Ranko ; Hranueli, Daslav ; Long, Paul F. ; Cullum, John ; Starčević, Antonio

engleski

Databases of the Thiotemplate Modular Systems (CSDB) and their in silico recombinants (r-CSDB)

Modular biosynthetic clusters are responsible for the synthesis of many important pharmaceutical products. They include polyketide synthases (PKS clusters), non-ribosomal synthetases (NRPS clusters), and mixed clusters (containing both PKS and NRPS modules). The ClustScan database (CSDB) contains highly annotated descriptions of 170 clusters. The database has a hierarchical organization, which allows easy extraction of DNA and protein sequences of polypeptides, modules, and domains as well as an organization of the annotation so as to be able to predict the product chemistry to view it or export it in a standard SMILES format. The recombinant ClustScan database contains information about predicted recombinants between PKS clusters. The recombinants are generated by modeling homologous recombination and are associated with annotation and prediction of product chemistry automatically generated by the model. The database contains over 20, 000 recombinants and is a resource for in silico approaches to detecting promising new compounds. Methods are available to construct the corresponding recombinants in the laboratory.

polyketide synthases; non-ribosomal synthetases; hybrid compounds; ClustScan; ClustScan database; predict annotation; modeling

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Podaci o izdanju

40 (6)

2013.

653-659

objavljeno

1367-5435

10.1007/s10295-013-1252-z

Povezanost rada

Biotehnologija

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