Zotchev Sergey B, Stepanchikova Alla V, Sergeyko Anastasia P, Sobolev Boris N, Filimonov Dmitrii A, Poroikov Vladimir V
Department of Biotechnology, Norwegian University of Science and Technology, Trondheim, Norway.
J Med Chem. 2006 Mar 23;49(6):2077-87. doi: 10.1021/jm051035i.
Bacterial secondary metabolites display diverse biological activities, thus having potential as pharmacological agents. Although most of these compounds are discovered by random screening, it is possible to predict and re-design their structures based on the information on their biosynthetic pathways. Biosynthesis of macrolides, governed by modular polyketide synthases (PKS), obeys certain rules, which can be simulated in silico. PKS mode of action theoretically allows for a huge number of macrolides to be produced upon combinatorial manipulation. Since engineering of all possible PKS variants is practically unfeasible, we created Biogenerator software, which simulates manipulation of PKS and generates virtual libraries of macrolides. These libraries can be screened by computer-aided prediction of biological activities, as exemplified by analysis of erythromycin and macrolactin libraries. This approach allows rational selection of macrolides with desired biological activities and provides instructions regarding the composition of the PKS gene clusters necessary for microbial production of such molecules.
细菌次级代谢产物具有多种生物活性,因此具有作为药物制剂的潜力。尽管这些化合物大多是通过随机筛选发现的,但根据其生物合成途径的信息来预测和重新设计它们的结构是可行的。由模块化聚酮合酶(PKS)控制的大环内酯类生物合成遵循一定的规则,这些规则可以在计算机上进行模拟。PKS的作用模式理论上允许通过组合操作产生大量的大环内酯类。由于对所有可能的PKS变体进行工程改造实际上是不可行的,我们创建了生物发生器软件,该软件模拟PKS的操作并生成大环内酯类的虚拟库。这些库可以通过计算机辅助的生物活性预测进行筛选,以红霉素和大环内酯菌素库的分析为例。这种方法允许合理选择具有所需生物活性的大环内酯类,并提供关于微生物生产此类分子所需的PKS基因簇组成的指导。