Complete biosynthesis of the bisbenzylisoquinoline alkaloids guattegaumerine and berbamunine in yeast

Benzylisoquinoline alkaloids (BIAs) are a diverse class of medicinal plant natural products. Nearly 500 dimeric bisbenzylisoquinoline alkaloids (bisBIAs), produced by the coupling of two BIA monomers, have been characterized and display a range of pharmacological properties, including anti-inflammatory, antitumor, and antiarrhythmic activities. In recent years, microbial platforms have been engineered to produce several classes of BIAs, which are rare or difficult to obtain from natural plant hosts, including protoberberines, morphinans, and phthalideisoquinolines. However, the heterologous biosyntheses of bisBIAs have thus far been largely unexplored. Here, we describe the engineering of yeast strains that produce the Type I bisBIAs guattegaumerine and berbamunine de novo. Through strain engineering, protein engineering, and optimization of growth conditions, a 10,000-fold improvement in the production of guattegaumerine, the major bisBIA pathway product, was observed. By replacing the cytochrome P450 used in the final coupling reaction with a chimeric variant, the product profile was inverted to instead produce solely berbamunine. Our highest titer engineered yeast strains produced 108 and 25 mg/L of guattegaumerine and berbamunine, respectively. Finally, the inclusion of two additional putative BIA biosynthesis enzymes, SiCNMT2 and NnOMT5, into our bisBIA biosynthetic strains enabled the production of two derivatives of bisBIA pathway intermediates de novo: magnocurarine and armepavine. The de novo heterologous biosyntheses of bisBIAs presented here provide the foundation for the production of additional medicinal bisBIAs in yeast.

Bisbenzylisoquinoline Alkaloids of Cissampelos Sympodialis With in Vitro Antiviral Activity Against Zika Virus

In search of new antiviral compounds against Zika virus we conducted a bioassay-guided fractionation of bisbenzyilisoquinoline alkaloids isolated from Cissampelos sympodialis (Menispermaceae), a medicinal plant species endemic to Brazil. Six subfractions were obtained from a tertiary alkaloidal fraction of the rhizomes (TAFrz) using preparative high-performance liquid chromatography. All the subfractions were tested against Zika virus-infected Vero cells as the cellular model to evaluate cytotoxicity and antiviral effective concentrations. The results showed that three of the six TAFrz subfractions tested were active. The most active ones were the subfraction 6 (that consisted of the alkaloids methylwarifteine and warifteine present as a mixture at a ratio of 8.8:1.2 respectively) and the subfraction 5, that was later identified as warifteine, the major tertiary alkaloid of this species. Warifteine was able to significantly reduce virus titer in Zika virus-infected Vero cells with an IC50 of 2.2 μg/ml and this effect was selective (selectivity index, SI = 68.3). Subfraction 6 had an IC50 = 3.5 μg/ml and was more cytotoxic than pure warifteine, with SI = 6.14. Fraction 5 and fraction 6 were more potent in decreasing the viral titer of Zika virus-infected Vero cells than 6-methylmercaptopurine riboside (IC50 = 24.5 μg/ml and SI = 11.9), a mercaptopurine riboside with ZIKV antiviral activity used as a positive control. Our data demonstrate that alkaloids of the bisbenzylisoquinoline type may be explored as new antiviral agents or as an useful pharmacophore for investigating ZIKV antiviral activity.

Molecular Docking Suggests the Targets of Anti-Mycobacterial Natural Products

Tuberculosis (TB) is a major global threat, mostly due to the development of antibiotic-resistant forms of Mycobacterium tuberculosis, the causal agent of the disease. Driven by the pressing need for new anti-mycobacterial agents several natural products (NPs) have been shown to have in vitro activities against M. tuberculosis. The utility of any NP as a drug lead is augmented when the anti-mycobacterial target(s) is unknown. To suggest these, we used a molecular reverse docking approach to predict the interactions of 53 selected anti-mycobacterial NPs against known “druggable” mycobacterial targets ClpP1P2, DprE1, InhA, KasA, PanK, PknB and Pks13. The docking scores/binding free energies were predicted and calculated using AutoDock Vina along with physicochemical and structural properties of the NPs, using PaDEL descriptors. These were compared to the established inhibitor (control) drugs for each mycobacterial target. The specific interactions of the bisbenzylisoquinoline alkaloids 2-nortiliacorinine, tiliacorine and 13′-bromotiliacorinine against the targets PknB and DprE1 (−11.4, −10.9 and −9.8 kcal·mol−1; −12.7, −10.9 and −10.3 kcal·mol−1, respectively) and the lignan α-cubebin and Pks13 (−11.0 kcal·mol−1) had significantly superior docking scores compared to controls. Our approach can be used to suggest predicted targets for the NP to be validated experimentally, but these in silico steps are likely to facilitate drug optimization.

The biology and total syntheses of bisbenzylisoquinoline alkaloids

This mini-review provides a concise overview of the biosynthetic pathway and pharmacology of bisbenzylisoquinoline alkaloid (bisBIA) natural products.

Molecular Docking Approaches to Suggest the Anti-Mycobacterial Targets of Natural Products

Tuberculosis (TB) is a major global threat mostly due to the development of antibiotic resistant forms of Mycobacterium tuberculosis, the causal agent of the disease. Driven by the pressing need for new anti-mycobacterial agents, several natural products (NPs) have been shown to have in vitro activities against M. tuberculosis. The utility of any NP as a drug lead is augmented when the anti-mycobacterial target(s) is unknown. To suggest these, we used a molecular docking approach to predict the interactions of 53 selected anti-mycobacterial NPs against known ‘druggable’ mycobacterial targets ClpP1P2, DprE1, InhA, KasA, PanK, PknB and Pks13. The docking scores / binding free energies were predicted and calculated using AutoDock Vina along with physicochemical and structural properties of the NPs, using PaDEL descriptors. These were compared to the established inhibitor (control) drugs for each mycobacterial target. The specific interactions of the bisbenzylisoquinoline alkaloids 2-nortiliacorinine, tiliacorine and 13’-bromotiliacorinine against the targets PknB and DprE1 (-11.4, -10.9 and -9.8 kcal.mol-1 ; -12.7, -10.9 and -10.3 kcal.mol-1 , respectively) and the lignan αcubebin and Pks13 (-11.0 kcal.mol-1 ) had significantly superior docking scores compared to controls. Our approach can be used to suggest predicted targets for the NP to be validated experimentally but these in silico steps are likely to facilitate drug optimisation.

Molecular Docking Approaches to Suggest the Anti-Mycobacterial Targets of Natural Products

Tuberculosis (TB) is a major global threat mostly due to the development of antibiotic resistant forms of Mycobacterium tuberculosis, the causal agent of the disease. Driven by the pressing need for new anti-mycobacterial agents, several natural products (NPs) have been shown to have in vitro activities against M. tuberculosis. The utility of any NP as a drug lead is augmented when the anti-mycobacterial target(s) is unknown. To suggest these, we used a molecular docking approach to predict the interactions of 53 selected anti-mycobacterial NPs against known ‘druggable’ mycobacterial targets ClpP1P2, DprE1, InhA, KasA, PanK, PknB and Pks13. The docking scores / binding free energies were predicted and calculated using AutoDock Vina along with physicochemical and structural properties of the NPs, using PaDEL descriptors. These were compared to the established inhibitor (control) drugs for each mycobacterial target. The specific interactions of the bisbenzylisoquinoline alkaloids 2-nortiliacorinine, tiliacorine and 13’-bromotiliacorinine against the targets PknB and DprE1 (-11.4, -10.9 and -9.8 kcal.mol-1 ; -12.7, -10.9 and -10.3 kcal.mol-1 , respectively) and the lignan αcubebin and Pks13 (-11.0 kcal.mol-1 ) had significantly superior docking scores compared to controls. Our approach can be used to suggest predicted targets for the NP to be validated experimentally but these in silico steps are likely to facilitate drug optimisation.