Synthesis of Ferulenol by Engineered Escherichia coli: Structural Elucidation by Using the In Silico Tools

Structural insights into the diverse prenylating capabilities of DMATS prenyltransferases

Covering: 2009 up to August 2023Prenyltransferases (PTs) are involved in the primary and the secondary metabolism of plants, bacteria, and fungi, and they are key enzymes in the biosynthesis of many clinically relevant natural products (NPs). The continued biochemical and structural characterization of the soluble dimethylallyl tryptophan synthase (DMATS) PTs over the past two decades have revealed the significant promise that these enzymes hold as biocatalysts for the chemoenzymatic synthesis of novel drug leads. This is a comprehensive review of DMATSs describing the structure-function relationships that have shaped the mechanistic underpinnings of these enzymes, as well as the application of this knowledge to the engineering of DMATSs. We summarize the key findings and lessons learned from these studies over the past 14 years (2009-2023). In addition, we identify current gaps in our understanding of these fascinating enzymes.

Unveiling the Potent Antiviral and Antioxidant Activities of an Aqueous Extract from Caesalpinia mimosoides Lamk: Cheminformatics and Molecular Docking Approaches

Our group previously demonstrated that Caesalpinia mimosoides Lamk exhibits many profound biological properties, including anticancer, antibacterial, and antioxidant activities. However, its antiviral activity has not yet been investigated. Here, the aqueous extract of C. mimosoides was prepared from the aerial parts (leaves, stalks, and trunks) to see whether it exerts anti-influenza (H1N1) effects and to reduce the organic solvents consumed during extraction, making it a desirable approach for the large-scale production for medical uses. Our plant extract was quantified to contain 7 g of gallic acid (GA) per 100 g of a dry sample, as determined using HPLC analysis. It also exerts potent antioxidant activities comparable to those of authentic GA. According to untargeted metabolomics (UPLC-ESI(-)-QTOF-MS/MS) with the aid of cheminformatics tools (MetFrag (version 2.1), SIRIUS (version 5.8.3), CSI:FingerID (version 4.8), and CANOPUS), the major metabolite was best annotated as "gallic acid", phenolics (e.g., quinic acid, shikimic acid, and protocatechuic acid), sugar derivatives, and dicarboxylic acids were deduced from this plant species for the first time. The aqueous plant extract efficiently inhibited an influenza A (H1N1) virus infection of MDCK cells with an IC50 of 5.14 µg/mL. Of equal importance, hemolytic activity was absent for this plant extract, signifying its applicability as a safe antiviral agent. Molecular docking suggested that GA interacts with conserved residues (e.g., Arg152 and Asp151) located in the catalytic inner shell of the viral neuraminidase (NA), sharing the same pocket as those of anti-neuraminidase drugs, such as laninamivir and oseltamivir. Additionally, other metabolites were also found to potentially interact with the active site and the hydrophobic 430-cavity of the viral surface protein, suggesting a possibly synergistic effect of various phytochemicals. Therefore, the C. mimosoides aqueous extract may be a good candidate for coping with increasing influenza virus resistance to existing antivirals.

Machine learning-assisted structure annotation of natural products based on MS and NMR data

Covering: up to March 2023Machine learning (ML) has emerged as a popular tool for analyzing the structures of natural products (NPs). This review presents a summary of the recent advancements in ML-assisted mass spectrometry (MS) and nuclear magnetic resonance (NMR) data analysis to establish the chemical structures of NPs. First, ML-based MS/MS analyses that rely on library matching are discussed, which involves the utilization of ML algorithms to calculate similarity, predict the MS/MS fragments, and form molecular fingerprint. Then, ML assisted MS/MS structural annotation without library matching is reviewed. Furthermore, the cases of ML algorithms in assisting structural studies of NPs based on NMR are discussed from four perspectives: NMR prediction, functional group identification, structural categorization and quantum chemical calculation. Finally, the review concludes with a discussion of the challenges and the trends associated with the structural establishment of NPs based on ML algorithms.

Microbial Metabolites Annotation by Mass Spectrometry-Based Metabolomics

Since the discovery of penicillin, microbial metabolites have been extensively investigated for drug discovery purposes. In the last decades, microbial derived compounds have gained increasing attention in different fields from pharmacognosy to industry and agriculture. Microbial metabolites in microbiomes present specific functions and can be associated with the maintenance of the natural ecosystems. These metabolites may exhibit a broad range of biological activities of great interest to human purposes. Samples from either microbial isolated cultures or microbiomes consist of complex mixtures of metabolites and their analysis are not a simple process. Mass spectrometry-based metabolomics encompass a set of analytical methods that have brought several improvements to the microbial natural products field. This analytical tool allows the comprehensively detection of metabolites, and therefore, the access of the chemical profile from those biological samples. These analyses generate thousands of mass spectra which is challenging to analyse. In this context, bioinformatic metabolomics tools have been successfully employed to accelerate and facilitate the investigation of specialized microbial metabolites. Herein, we describe metabolomics tools used to provide chemical information for the metabolites, and furthermore, we discuss how they can improve investigation of microbial cultures and interactions.

Discovering New Natural Products Using Metabolomics-Based Approaches

The incessant search for new natural molecules with biological activities has forced researchers in the field of chemistry of natural products to seek different approaches for their prospection studies. In particular, researchers around the world are turning to approaches in metabolomics to avoid high rates of re-isolation of certain compounds, something recurrent in this branch of science. Thanks to the development of new technologies in the analytical instrumentation of spectroscopic and spectrometric techniques, as well as the advance in the computational processing modes of the results, metabolomics has been gaining more and more space in studies that involve the prospection of natural products. Thus, this chapter summarizes the precepts and good practices in the metabolomics of microbial natural products using mass spectrometry and nuclear magnetic resonance spectroscopy, and also summarizes several examples where this approach has been applied in the discovery of bioactive molecules.