Natural products represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs, anticancer therapies, and immunomodulatory agents. These molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms, although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers reduced false positive rates in BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing machine-learning tools. We supplemented this with random forest classifiers that accurately predicted BGC product classes and potential chemical activity. Application of DeepBGC to bacterial genomes uncovered previously undetectable putative BGCs that may code for natural products with novel biologic activities. The improved accuracy and classification ability of DeepBGC represents a major addition to in-silico BGC identification.

• MeSH
• biosyntetické dráhy genetika   MeSH
• data mining metody   MeSH
• deep learning MeSH
• genom bakteriální genetika   MeSH
• genom MeSH
• multigenová rodina genetika   MeSH
• výpočetní biologie metody   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

This review aims at comparing some historical data with the current situation in the study of biogenesis of natural compounds, antibiotics in the first place. Biogenesis of tetracyclines and cycloheximide and related compounds serves as example. Examples of molecular biological and bioinformatics methods used in the study of antibiotic biogenesis are described both in terms of its historical aspects and the current knowledge.

• MeSH
• antibakteriální látky biosyntéza   metabolismus   MeSH
• dějiny 20. století MeSH
• dějiny 21. století MeSH
• metabolické sítě a dráhy genetika   MeSH
• objevování léků dějiny   MeSH
• výpočetní biologie MeSH
• Check Tag
• dějiny 20. století MeSH
• dějiny 21. století MeSH
• Publikační typ
• časopisecké články MeSH
• historické články MeSH
• přehledy MeSH
• Názvy látek
• antibakteriální látky MeSH

Using the examples of biosynthesis of streptomycin, bialaphos, actinorhodin, oligoketides and autoregulators during the first hours of streptomycete cultivation, it is stressed that the external environment in cooperation with the internal metabolic abilities of the cell determines the metabolic type that would develop during the life cycle of the producing streptomycetes. If we accept that a certain metabolic type (from the point of view of the production of secondary metabolites) was determined already during the first hours of cultivation of the microorganisms, we must also admit that the availability of primary metabolites in the so-called production phase of growth (stationary phase, idiophase, etc.) is to a certain extent determined by the very early stages of strain development.

• MeSH
• anthrachinony metabolismus   MeSH
• antibakteriální látky biosyntéza   MeSH
• časové faktory MeSH
• organofosforové sloučeniny metabolismus   MeSH
• regulace genové exprese u bakterií MeSH
• Streptomyces fyziologie   MeSH
• streptomycin biosyntéza   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH
• Názvy látek
• actinorhodin MeSH Prohlížeč
• anthrachinony MeSH
• antibakteriální látky MeSH
• bialaphos MeSH Prohlížeč
• organofosforové sloučeniny MeSH
• streptomycin MeSH