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Related Experiment Video

Updated: May 28, 2026

From a Natural Product to Its Biosynthetic Gene Cluster: A Demonstration Using Polyketomycin from Streptomyces diastatochromogenes T&#252;6028
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From a Natural Product to Its Biosynthetic Gene Cluster: A Demonstration Using Polyketomycin from Streptomyces diastatochromogenes Tü6028

Published on: January 13, 2017

Recombinatorial biosynthesis of polyketides.

Antonio Starcevic1, Kerstin Wolf, Janko Diminic

  • 1University of Zagreb, Zagreb, Croatia.

Journal of Industrial Microbiology & Biotechnology
|November 2, 2011
PubMed
Summary

CompGen software enables in silico homologous recombination of polyketide synthase (PKS) gene clusters. This generates a diverse library of novel polyketide structures for drug discovery.

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From a Natural Product to Its Biosynthetic Gene Cluster: A Demonstration Using Polyketomycin from Streptomyces diastatochromogenes T&#252;6028
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A Customizable Approach for the Enzymatic Production and Purification of Diterpenoid Natural Products
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A Customizable Approach for the Enzymatic Production and Purification of Diterpenoid Natural Products

Published on: October 4, 2019

Area of Science:

  • Biotechnology
  • Synthetic Biology
  • Cheminformatics

Background:

  • Modular polyketide synthases (PKSs) in Streptomyces are crucial for producing pharmaceuticals.
  • Understanding PKS gene cluster recombination is key to discovering new drug compounds.

Purpose of the Study:

  • To develop a computational tool (CompGen) for in silico homologous recombination of PKS gene clusters.
  • To predict the structures of novel polyketides generated by recombinant PKS systems.
  • To create a database (r-CSDB) of these virtual compounds for drug design.

Main Methods:

  • Development of the CompGen program for in silico homologous recombination.
  • Application of CompGen to 47 characterized PKS gene clusters.
  • Prediction of chemical structures, molecular weights, and average degrees of reduction for recombinant polyketides.
  • Creation of the r-CSDB database.

Main Results:

  • In silico recombination of 47 PKS clusters predicted 11,796 unique polyketide structures.
  • Predicted structures exhibit diverse molecular weights and reduction degrees, suggesting pharmaceutical potential.
  • The r-CSDB database now houses these novel virtual compounds.

Conclusions:

  • CompGen is a valuable tool for exploring PKS diversity and generating novel chemical entities.
  • The r-CSDB database serves as a resource for computer-aided drug design and chemoinformatics.
  • Experimental strategies for constructing recombinant Streptomyces strains are feasible.