New methods for isolation and structure determination of natural products

Roger G. Linington *a, Julia Kubanek b and Hendrik Luesch c
aDepartment of Chemistry, Simon Fraser University, Burnaby, Canada. E-mail:
bSchool of Biological Sciences, Aquatic Chemical Ecology Center, Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, USA
cDepartment of Medicinal Chemistry, College of Pharmacy, Center for Natural Products, Drug Discovery and Development (CNPD3), University of Florida, Gainesville, USA

Natural products research is an area of science that is heavily influenced by analytical technologies. Because structure elucidation is the rate limiting step for many projects, advances in this area have a disproportionate effect on the direction of the field. After a period of relative inactivity in technology deployment, we are now enjoying an ‘analytical revolution’, with numerous new discovery modalities becoming available as mainstream tools. This themed issue on New Methods for Isolation and Structure Determination of Natural Products aims to highlight some of these new developments, and to illustrate how these technologies are being employed to answer new and previously inaccessible questions in our field.

Arguably the single most important development for structure elucidation in the history of natural products research was the development of HMBC and HMQC NMR pulse programs in 1983 and 1986, respectively.1,2 Prior to this, structure elucidation was often a multi-year affair requiring meticulous chemical degradation and derivatization studies. Exemplars of this art form include the discoveries of both strychnine3 and palytoxin,4–6 each of which took many years to resolve. The natural products community was quick to recognize the potential of the new NMR technology and by the early 1990’s most structure elucidation projects were employing the HMBC and HMQC approach. Since then, interpretation of the data has been largely by manual inspection and interpretation. In this themed issue, Burns et al. discuss developments in computer assisted structure elucidation (CASE; Burns et al., DOI: 10.1039/c9np00007k) and summarize the advantages and limitations of four of the most widely used CASE platforms.

Less immediate, but similarly important, developments in mass spectrometry have heavily influenced the field over the last 40 years. At the turn of the millennium, most accurate mass instruments were managed by skilled technicians in dedicated mass spectrometry facilities. Thanks to advancements in hardware accuracy and reliability it is now common to see high resolution instruments located in individual research laboratories, run by research scientists who are not mass spectrometry specialists. This democratization of the technology has opened a door to the development of numerous resources for natural products chemists. These include new sampling modalities, such as the droplet probe for mass spectrometric analysis of microbial colonies and surfaces (Oberlies et al., DOI: 10.1039/c9np00019d), and new data analysis platforms. Fox Ramos et al. provide a summary of the latest applications of the molecular networking/global natural products social network (GNPS) infrastructure.7–9 This review includes both a discussion of recent efforts to integrate molecular networking data with other orthogonal data types and a summary of rules and recommendations for successful data analysis using this platform (Fox Ramos et al., DOI: 10.1039/c9np00006b).

Having determined the planar structure of a given natural product, the next challenge is often configurational assignment. In fact, many natural products were initially assigned erroneous configurations, a problem commonly discovered only years later, following tour-de-force total syntheses of the proposed published structure and (unnatural) structural analogues. This obviously negatively impacts the synthetic and medicinal chemistry communities. Beyond the disappointment associated with synthesizing molecules that do not match the published spectral data, these misassignments can lead to substantial wasted effort during drug development programs, given that the three-dimensional structure of natural products is of utmost importance for their biological activities. Traditionally, configurational analysis has relied on a combination of coupling constant and nuclear Overhauser effect data from NMR experiments, degradation and derivatization approaches (e.g., Marfey’s,10 Mosher’s ester11) and, where possible, X-ray crystallography. Computational tools are now advancing to a point where additional analytical methods, including ECD, VCD, and ORD, are accessible to the natural products community. This significantly extends the number of situations in which configurational assignments can be made on complex products with limited supply. Mándi and Kurtán present an overview of these analytical techniques, and summarize recent applications in the area of natural products configurational analysis (Mándi and Kurtán, DOI: 10.1039/c9np00002j). In a second article on this topic, Grauso et al. discuss current computational methods for predicting spectra for these techniques, including strategies for handling solvent effects and multi-conformer molecules (Grauso et al., DOI: 10.1039/c9np00018f).

In the area of natural product isolation, three articles present areas of innovation from across the full discovery workflow. Berlinck et al. summarize recent developments in the isolation of natural products with challenging physical properties. These natural products include water soluble compounds, volatiles and highly reactive compounds, as well as compounds present in very low quantities (Berlink et al., DOI: 10.1039/c9np00009g). The issue of synergistic and antagonistic interactions in natural products discovery is covered in detail by Caesar and Cech (DOI: 10.1039/c9np00011a). This review presents both the impact of synergistic interactions on bioassay-guided isolation, as well as metabolomics approaches to identifying synergists. Finally, natural products science is beginning to embrace omics integration, where information from orthogonal profiling datasets is combined to identify relationships between the datasets (e.g., metabolomics and screening data). This subject is covered by Wolfender et al., who discuss prioritization strategies for natural products discovery, using a range of profiling tools (Wolfender et al., DOI: 10.1039/c9np00004f).

Together these articles provide an exciting perspective on the direction of the field of natural products discovery. As compound identification becomes faster and more straightforward, we expect to see a concomitant shift in the field towards systems-based analysis methods for many projects. The promise of a time in the near future where molecules can be identified in minutes or hours rather than weeks changes both the scale of analysis we can attempt, and the types of questions we can ask. Analytical technologies will continue to play a central role in this development, including many of the methods covered in this themed issue.


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