Recent advances and new strategies in the NMR-based identification of natural products

Dereplication: racing to speed up the natural products discovery process

Covering: 1993-2014 (July)To alleviate the dereplication holdup, which is a major bottleneck in natural products discovery, scientists have been conducting their research efforts to add tools to their "bag of tricks" aiming to achieve faster, more accurate and efficient ways to accelerate the pace of the drug discovery process. Consequently dereplication has become a hot topic presenting a huge publication boom since 2012, blending multidisciplinary fields in new ways that provide important conceptual and/or methodological advances, opening up pioneering research prospects in this field.

Current status and prospects of computational resources for natural product dereplication: a review

Research in natural products has always enhanced drug discovery by providing new and unique chemical compounds. However, recently, drug discovery from natural products is slowed down by the increasing chance of re-isolating known compounds. Rapid identification of previously isolated compounds in an automated manner, called dereplication, steers researchers toward novel findings, thereby reducing the time and effort for identifying new drug leads. Dereplication identifies compounds by comparing processed experimental data with those of known compounds, and so, diverse computational resources such as databases and tools to process and compare compound data are necessary. Automating the dereplication process through the integration of computational resources has always been an aspired goal of natural product researchers. To increase the utilization of current computational resources for natural products, we first provide an overview of the dereplication process, and then list useful resources, categorizing into databases, methods and software tools and further explaining them from a dereplication perspective. Finally, we discuss the current challenges to automating dereplication and proposed solutions.

RNAi-based biosynthetic pathway screens to identify in vivo functions of non-nucleic acid-based metabolites such as lipids

The field of metabolomics continues to catalog new compounds, but their functional analysis remains technically challenging, and roles beyond metabolism are largely unknown. Unbiased genetic/RNAi screens are powerful tools to identify the in vivo functions of protein-encoding genes, but not of nonproteinaceous compounds such as lipids. They can, however, identify the biosynthetic enzymes of these compounds-findings that are usually dismissed, as these typically synthesize multiple products. Here, we provide a method using follow-on biosynthetic pathway screens to identify the endpoint biosynthetic enzyme and thus the compound through which they act. The approach is based on the principle that all subsequently identified downstream biosynthetic enzymes contribute to the synthesis of at least this one end product. We describe how to systematically target lipid biosynthetic pathways; optimize targeting conditions; take advantage of pathway branchpoints; and validate results by genetic assays and biochemical analyses. This approach extends the power of unbiased genetic/RNAi screens to identify in vivo functions of non-nucleic acid-based metabolites beyond their metabolic roles. It will typically require several months to identify a metabolic end product by biosynthetic pathway screens, but this time will vary widely depending, among other factors, on the end product's location in the pathway, which determines the number of screens required for its identification.

Open-access metabolomics databases for natural product research: present capabilities and future potential

Various databases have been developed to aid in assigning structures to spectral peaks observed in metabolomics experiments. In this review article, we discuss the utility of currently available open-access spectral and chemical databases for natural products discovery. We also provide recommendations on how the research community can contribute to further improvements.

The re-emergence of natural products for drug discovery in the genomics era

Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery.

The past, present and future of secondary metabolite research in the Dothideomycetes

The Dothideomycetes represents a large and diverse array of fungi in which prominent plant pathogens are over-represented. Species within the Cochliobolus, Alternaria, Pyrenophora and Mycosphaerella (amongst others) all cause diseases that threaten food security in many parts of the world. Significant progress has been made over the past decade in understanding how some of these pathogens cause disease at a molecular level. It is reasonable to suggest that much of this progress can be attributed to the increased availability of genome sequences. However, together with revealing mechanisms of pathogenicity, these genome sequences have also highlighted the capacity of the Dothideomycetes to produce an extensive array of secondary metabolites, far greater than originally thought. Indeed, it is now clear that we appear to have only scratched the surface to date in terms of the identification of secondary metabolites produced by these fungi. In the first half of this review, we examine the current status of secondary metabolite research in the Dothideomycetes and highlight the diversity of the molecules discovered thus far, in terms of both structure and biological activity. In the second part of this review, we survey the emerging techniques and technologies that will be required to shed light on the vast array of secondary metabolite potential that is encoded within these genomes. Experimental design, analytical chemistry and synthetic biology are all discussed in the context of how they will contribute to this field.

Two dimensional NMR spectroscopic approaches for exploring plant metabolome: A review

Today, most investigations of the plant metabolome tend to be based on either nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry (MS), with or without hyphenation with chromatography. Although less sensitive than MS, NMR provides a powerful complementary technique for the identification and quantification of metabolites in plant extracts. NMR spectroscopy, well appreciated by phytochemists as a particularly information-rich method, showed recent paradigm shift for the improving of metabolome(s) structural and functional characterization and for advancing the understanding of many biological processes. Furthermore, two dimensional NMR (2D NMR) experiments and the use of chemometric data analysis of NMR spectra have proven highly effective at identifying novel and known metabolites that correlate with changes in genotype or phenotype. In this review, we provide an overview of the development of NMR in the field of metabolomics with special focus on 2D NMR spectroscopic techniques and their applications in phytomedicines quality control analysis and drug discovery from natural sources, raising more attention at its potential to reduce the gap between the pace of natural products research and modern drug discovery demand.

LR-HSQMBC: a sensitive NMR technique to probe very long-range heteronuclear coupling pathways

HMBC is one of the most often used and vital NMR experiments for the structure elucidation of organic and inorganic molecules. We have developed a new, high sensitivity NMR pulse sequence that overcomes the typical (2,3)JCH limitation of HMBC by extending the visualization of long-range correlation data to 4-, 5-, and even 6-bond long-range (n)JCH heteronuclear couplings. This technique should prove to be an effective experiment to complement HMBC for probing the structure of proton-deficient molecules. The LR-HSQMBC NMR experiment can, in effect, extend the range of HMBC to provide data similar to that afforded by 1,n-ADEQUATE even in sample-limited situations. This is accomplished by optimizing responses for very small (n)JCH coupings as opposed to relying on the markedly less sensitive detection of long-range coupled (13)C-(13)C homonuclear pairs at natural abundance. DFT calculations were employed to determine whether the very long-range correlations observed for cervinomycin A2 were reasonable on the basis of the calculated long-range couplings.