| Literature DB >> 34069975 |
Moon Sajid1, Chaitanya N Channakesavula1, Shane R Stone1, Parwinder Kaur1.
Abstract
Flavonoids are a structurally diverse class of natural products that have been found to have a range of beneficial activities in humans. However, the clinical utilisation of these molecules has been limited due to their low solubility, chemical stability, bioavailability and extensive intestinal metabolism in vivo. Recently, the view has been formed that site-specific modification of flavonoids by methylation and/or glycosylation, processes that occur in plants endogenously, can be used to improve and adapt their biophysical and pharmacokinetic properties. The traditional source of flavonoids and their modified forms is from plants and is limited due to the low amounts present in biomass, intrinsic to the nature of secondary metabolite biosynthesis. Access to greater amounts of flavonoids, and understanding of the impact of modifications, requires a rethink in terms of production, more specifically towards the adoption of plant biosynthetic pathways into ex planta synthesis approaches. Advances in synthetic biology and metabolic engineering, aided by protein engineering and machine learning methods, offer attractive and exciting avenues for ex planta flavonoid synthesis. This review seeks to explore the applications of synthetic biology towards the ex planta biosynthesis of flavonoids, and how the natural plant methylation and glycosylation pathways can be harnessed to produce modified flavonoids with more favourable biophysical and pharmacokinetic properties for clinical use. It is envisaged that the development of viable alternative production systems for the synthesis of flavonoids and their methylated and glycosylated forms will help facilitate their greater clinical application.Entities:
Keywords: anticancer compounds; ex planta synthesis; flavonoids; pharmacokinetics
Year: 2021 PMID: 34069975 PMCID: PMC8157843 DOI: 10.3390/biom11050754
Source DB: PubMed Journal: Biomolecules ISSN: 2218-273X
Figure 1Basic flavonoid backbone and structure of most common sub-classes.
Chemical and biophysical properties, and challenges of flavonoids in planta production. Table 2. Examples of de novo flavonoids biosynthesis in microbes.
| Properties | Flavonoid Characteristics | |
|---|---|---|
| Solubility | Low intestinal absorption making it difficult to attain pharmacologically effective concentration in-vivo | [ |
| Chemical stability | Difficulties in extraction and long-term storage | [ |
| Metabolic stability | Different substitutions on basic skeleton results in lower activity, and inertness which finally leads to excretion | [ |
|
| ||
| Yield | Very low yield of plant secondary metabolites relative to biomass | [ |
| Purity | Heterogeneous mixtures difficult to assign a particular function to a specific molecule | [ |
| Biosynthesis | Regulatory and bioengineering challenges in genetic engineering to increase yield | [ |
| Isolation and extraction | Loss in activity due to degradation and alteration in chemical structure | [ |
Figure 2Diagrammatic representation of methylated flavonoids (schematic flavonoid is a hypothetical compound used to show all hydroxyl positions accessible for methylation).
Figure 3Diagrammatic representation of glycosylated flavonoids (schematic flavonoid is a hypothetical compound used to show all hydroxyl positions accessible for glycosylation).
Figure 4Microbial systems, cell-free systems and cell-free glycosylation approaches are used to synthesize flavonoids with an improved PK profile. To produce commercially viable titer, rate and yield (TRY), machine-learning approaches like DeepCRISPR and sgRNA can help in the genetic engineering of microbial systems and gene regulatory network (GRN) analysis tools can help in the construction of new metabolic pathways. Similarly, protein engineering approaches can also help flavonoid biosynthesis through reproposing enzymes for better activity and stability, as well as by de novo synthesis of enzymes for the production of new-to-nature flavonoid derivatives. Abbreviations: CNNC; convolutional neural network for coexpression, GripDL; gene regulatory interaction prediction via deep learning, NHEJ; non-homologous end joining, HDR; homology directed recombination.
Examples of de novo flavonoids biosynthesis in microbes.
| Scheme | Compound | Host Organism | Precursors | Titer or Productivity (mg/L) | Approaches | Reference | |
|---|---|---|---|---|---|---|---|
| Initial | Final | ||||||
| Flavanones | Pinocembrin |
| Glucose | 102.0 | 165.3 | Managing precursors balance in prokaryotic cell to achieve highest possible yield | [ |
| Naringenin |
| D-glucose | 90.59 | 100.64 | Engineering primary metabolism to increase heterologous synthesis of flavonoids | [ | |
| Naringenin |
| Xylose | 239.1 | 715.3 | Engineering xylose metabolism to increase heterologous synthesis of flavonoids | [ | |
| Eriodictyol |
| Sucrose | - | 0.002 | Exploration of new host for industrial production of flavonoids | [ | |
| Flavones | Apigenin |
| Sucrose | - | 0.08 | Exploration of new host for industrial production of flavonoids | [ |
| Chrysin |
| Phenylalanine | - | 9.4 | Functional expression of plant enzymes in prokaryotic system | [ | |
| Scutellarein |
| L-tyrosine | 47.1 | 106.5 | Expression of plant P450 enzyme and precursor balancing in prokaryotic system | [ | |
| Flavonols | Kaempferol |
| Sucrose and glycerol | 86 | 200 | Co-culturing for management of metabolic burden and gene expression | [ |
| Quercetin |
| Sucrose | - | 0.1 | De novo synthesis of flavonoids in industrial actinomycetes | [ | |
| Galangin |
| Phenylalanine | - | 1.1 | Functional expression of plant enzymes in prokaryotic system | [ | |
| Isoflavanones | Genistin |
| Genistein | - | 75.9 | Bioconversion of isoflavonoids into their glycosylated forms | [ |
| 4′-O-methyl daidzein |
| Daidzein | 49.4 | 102.8 | Enzyme screening and precursor management for synthesis of flavonoid derivatives | [ | |
| 4′-O-methyl genistein |
| Genistein | 25.7 | 46.8 | Enzyme screening and precursor management for synthesis of flavonoid derivatives | [ | |