Spatio-temporal expression of polyphenol oxidase unveils the dynamics of L-DOPA accumulation in faba bean (Vicia faba L.).

Faba bean (Vicia faba L.) is a winter season grain legume and a rich source of the anti-parkinson drug, L-3,4-dihydroxyphenylalanine (L-DOPA). The biosynthesis of L-DOPA in plants is not uniform and remains largely unexplored. While the hydroxylase activities of Tyrosine Hydroxylase (TH), the Cytochrome P450 (CYP450) class of enzymes, and Polyphenol Oxidases (PPOs) on tyrosine substrate have been reported in plants, only the roles of PPOs in L-DOPA biosynthesis have been recently established in velvet bean (Mucuna pruriens). To understand the differential accumulation of L-DOPA in different tissues of faba bean, profiling of L-Tyrosine, L-DOPA, Tyramine, and Dopamine in different tissues was performed. Differential accumulation of L-DOPA depended on tissue type and maturity. Furthermore, dopamine biosynthesis through L-DOPA from L-Tyr was confirmed in faba bean. The expression analysis of PPOs in leaf and flower tissues revealed the selective induction of only four (HePPO-2, HePPO-7, HePPO-8b, and HePPO-10) out of ten genes encoding different PPOs mined from the faba bean genome. Higher accumulation of L-DOPA in young leaves and flower buds than in mature leaves and flowers was accompanied by significantly higher expression of HePPO-10 and HePPO-7, respectively. The role of various transcription factors contributing to such metabolite dynamics was also predicted. Further exploration of this mechanism using a multi-omics approach can provide meaningful insight and pave the way for enhancing L-DOPA content in crops. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01449-2.

Metabolic Pathway Reconstruction Indicates the Presence of Important Medicinal Compounds in Coffea Such as L-DOPA.

The use of transcriptomic data to make inferences about plant metabolomes is a useful tool to help the discovery of important compounds in the available biodiversity. To unveil previously undiscovered metabolites of Coffea, of phytotherapeutic and economic value, we employed 24 RNAseq libraries. These libraries were sequenced from leaves exposed to a diverse range of environmental conditions. Subsequently, the data were meticulously processed to create models of putative metabolic networks, which shed light on the production of potential natural compounds of significant interest. Then, we selected one of the predicted compounds, the L-3,4-dihydroxyphenylalanine (L-DOPA), to be analyzed by LC-MS/MS using three biological replicates of flowers, leaves, and fruits from Coffea arabica and Coffea canephora. We were able to identify metabolic pathways responsible for producing several compounds of economic importance. One of the identified pathways involved in isoquinoline alkaloid biosynthesis was found to be active and producing L-DOPA, which is a common product of POLYPHENOL OXIDASES (PPOs, EC 1.14.18.1 and EC 1.10.3.1). We show that coffee plants are a natural source of L-DOPA, a widely used medicine for treatment of the human neurodegenerative condition called Parkinson's disease. In addition, dozens of other compounds with medicinal significance were predicted as potential natural coffee products. By further refining analytical chemistry techniques, it will be possible to enhance the characterization of coffee metabolites, enabling a deeper understanding of their properties and potential applications in medicine.

Pharmacoinformatics exploration of polyphenol oxidases leading to novel inhibitors by virtual screening and molecular dynamic simulation study.

Polyphenol oxidases (PPOs)/tyrosinases are metal-dependent enzymes and known as important targets for melanogenesis. Although considerable attempts have been conducted to control the melanin-associated diseases by using various inhibitors. However, the exploration of the best anti-melanin inhibitor without side effect still remains a challenge in drug discovery. In present study, protein structure prediction, ligand-based pharmacophore modeling, virtual screening, molecular docking and dynamic simulation study were used to screen the strong novel inhibitor to cure melanogenesis. The 3D structures of PPO1 and PPO2 were built through homology modeling, while the 3D crystal structures of PPO3 and PPO4 were retrieved from PDB. Pharmacophore modeling was performed using LigandScout 3.1 software and top five models were selected to screen the libraries (2601 of Aurora and 727, 842 of ZINC). Top 10 hit compounds (C1-10) were short-listed having strong binding affinities for PPO1-4. Drug and synthetic accessibility (SA) scores along with absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment were employed to scrutinize the best lead hit. C4 (name) hit showed the best predicted SA score (5.75), ADMET properties and drug-likeness behavior among the short-listed compounds. Furthermore, docking simulations were performed to check the binding affinity of C1-C10 compounds against target proteins (PPOs). The binding affinity values of complex between C4 and PPOs were higher than those of other complexes (-11.70, -12.1, -9.90 and -11.20kcal/mol with PPO1, PPO2, PPO3, or PPO4, respectively). From comparative docking energy and binding analyses, PPO2 may be considered as better target for melanogenesis than others. The potential binding modes of C4, C8 and C10 against PPO2 were explored using molecular dynamics simulations. The root mean square deviation and fluctuation (RMSD/RMSF) graphs results depict the significance of C4 over the other compounds. Overall, bioactivity and ligand efficiency profiles suggested that the proposed hit may be more effective inhibitors for melanogenesis.