Naslov
Prediction of compounds of potential agricultural interest from DNA sequences using the ClustScan program

Autori
Žučko, Jurica ; Cullum, John ; Hranueli, Daslav

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
4th Central European Congress on Food & 6th Croatian Congress of Food Techologists, Biotechnologists, and Nutritionists : Book of abstracts / Karlović, Damir - Zagreb : Hrvatsko društvo za prehrambenu tenologiju, biotehnologiju i nutricionizam, 2008, 215 (P_150)-215 (P_150)

ISBN
978-953-99725-2-1

Skup
Central European Meeting of Food Technologists, Biotechnologists and Nutritionists (4 ; 2008) ; Croatian Congress of Food Technologists, Biotechnologists and Nutritionists (6 ; 2008)

Mjesto i datum
Cavtat, Hrvatska, 15.05.2008. - 17.05.2008

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
polyketides; antiparasitics; coccidiostatics; annotation

Sažetak
Secondary metabolites play an important role in agricultural production. They include antiparasitics as well as coccidiostatics and animal growth promoters. Polyketides are one of the most important chemical classes. Many products are synthesised by modular polyketide synthetases (PKS) in bacteria. In this case, successive biosynthesis steps are carried out in successive modules in the PKS. Each module incorporates a module-specific extender unit. The variety of choice for extender unit allows the synthesis of a large number of different polyketides. The extender units can differ in number of carbon atoms (C2, C3 or larger) and the degree of reduction (keto group, hydroxyl group, C=C double bond or fully reduced) as well as different chiral forms. Comparing the DNA sequences of modules from well-characterised clusters has given information about protein sequence differences associated with the incorporation of different extender units. Large scale DNA sequencing is resulting in ever increasing numbers of sequenced PKS clusters, whose product is unknown. We have developed the program ClustScan, which helps the semi-automatic annotation of unknown modular PKS clusters including prediction of the extender units incorporated by each module. We will show the results of such analyses and discuss the limits of prediction and the problem of selecting clusters, which may produce products of agricultural interest for further characterisation.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Biologija, Biotehnologija

POVEZANOST RADA