Computational Approach for the Analysis of Post-PKS Glycosylation Step

We introduce a computational approach for analysis of glycosylation in Post-PKS tailoring steps. It is a computational method to predict the deoxysugar biosynthesis unit pathway and the substrate specificity of glycosyltransferases involved in the glycosylation of polyketides. In this work, a directed and weighted graph is introduced to represent and predict the deoxysugar biosynthesis unit pathway. In addition, a homology based gene clustering method is used to predict the substrate specificity of glycosyltransferases. It is useful for the rational design of polyketide natural products, which leads to in silico drug discovery.

Computational Approach for Biosynthetic Engineering of Post-PKS Tailoring Enzymes

Compounds of polyketide origin possess a wealth of pharmacological effects, including antibacterial, antifungal, antiparasitic, anticancer and immunosuppressive activities. Many of these compounds and their semisynthetic derivatives are used today in the clinic. Most of the gene clusters encoding commercially important drugs have also been cloned and sequenced and their biosynthetic mechanisms studied in great detail. The area of biosynthetic engineering of the enzymes involved in polyketide biosynthesis has recently advanced and been transferred into the industrial arena. In this work, we introduce a computational system to provide the user with a wealth of information that can be utilized for biosynthetic engineering of enzymes involved in post-PKS tailoring steps. Post-PKS tailoring steps are necessary to add functional groups essential for the biological activity and are therefore important in polyketide biosynthesis.