Review on natural products databases: where to find data in 2020

Plant-derived nanotherapeutic systems to counter the overgrowing threat of resistant microbes and biofilms

Since antiquity, the survival of human civilization has always been threatened by the microbial infections. An alarming surge in the resistant microbial strains against the conventional drugs is quite evident in the preceding years. Furthermore, failure of currently available regimens of antibiotics has been highlighted by the emerging threat of biofilms in the community and hospital settings. Biofilms are complex dynamic composites rich in extracellular polysaccharides and DNA, supporting plethora of symbiotic microbial life forms, that can grow on both living and non-living surfaces. These enforced structures are impervious to the drugs and lead to spread of recurrent and non-treatable infections. There is a strong realization among the scientists and healthcare providers to work out alternative strategies to combat the issue of drug resistance and biofilms. Plants are a traditional but rich source of effective antimicrobials with wider spectrum due to presence of multiple constituents in perfect synergy. Other than the biocompatibility and the safety profile, these phytochemicals have been repeatedly proven to overcome the non-responsiveness of resistant microbes and films via multiple pathways such as blocking the efflux pumps, better penetration across the cell membranes or biofilms, and anti-adhesive properties. However, the unfavorable physicochemical attributes and stability issues of these phytochemicals have hampered their commercialization. These issues of the phytochemicals can be solved by designing suitably constructed nanoscaled structures. Nanosized systems can not only improve the physicochemical features of the encapsulated payloads but can also enhance their pharmacokinetic and therapeutic profile. This review encompasses why and how various types of phytochemicals and their nanosized preparations counter the microbial resistance and the biofouling. We believe that phytochemical in tandem with nanotechnological innovations can be employed to defeat the microbial resistance and biofilms. This review will help in better understanding of the challenges associated with developing such platforms and their future prospects.

Towards the De Novo Design of HIV-1 Protease Inhibitors Based on Natural Products

Acquired immunodeficiency syndrome (AIDS) caused by the human immunodeficiency virus (HIV) continues to be a public health problem. In 2020, 680,000 people died from HIV-related causes, and 1.5 million people were infected. Antiretrovirals are a way to control HIV infection but not to cure AIDS. As such, effective treatment must be developed to control AIDS. Developing a drug is not an easy task, and there is an enormous amount of work and economic resources invested. For this reason, it is highly convenient to employ computer-aided drug design methods, which can help generate and identify novel molecules. Using the de novo design, novel molecules can be developed using fragments as building blocks. In this work, we develop a virtual focused compound library of HIV-1 viral protease inhibitors from natural product fragments. Natural products are characterized by a large diversity of functional groups, many sp3 atoms, and chiral centers. Pseudo-natural products are a combination of natural products fragments that keep the desired structural characteristics from different natural products. An interactive version of chemical space visualization of virtual compounds focused on HIV-1 viral protease inhibitors from natural product fragments is freely available in the supplementary material.

NP-MRD: the Natural Products Magnetic Resonance Database

The Natural Products Magnetic Resonance Database (NP-MRD) is a comprehensive, freely available electronic resource for the deposition, distribution, searching and retrieval of nuclear magnetic resonance (NMR) data on natural products, metabolites and other biologically derived chemicals. NMR spectroscopy has long been viewed as the ‘gold standard’ for the structure determination of novel natural products and novel metabolites. NMR is also widely used in natural product dereplication and the characterization of biofluid mixtures (metabolomics). All of these NMR applications require large collections of high quality, well-annotated, referential NMR spectra of pure compounds. Unfortunately, referential NMR spectral collections for natural products are quite limited. It is because of the critical need for dedicated, open access natural product NMR resources that the NP-MRD was funded by the National Institute of Health (NIH). Since its launch in 2020, the NP-MRD has grown quickly to become the world's largest repository for NMR data on natural products and other biological substances. It currently contains both structural and NMR data for nearly 41,000 natural product compounds from >7400 different living species. All structural, spectroscopic and descriptive data in the NP-MRD is interactively viewable, searchable and fully downloadable in multiple formats. Extensive hyperlinks to other databases of relevance are also provided. The NP-MRD also supports community deposition of NMR assignments and NMR spectra (1D and 2D) of natural products and related meta-data. The deposition system performs extensive data enrichment, automated data format conversion and spectral/assignment evaluation. Details of these database features, how they are implemented and plans for future upgrades are also provided. The NP-MRD is available at https://np-mrd.org.

Advancements in capturing and mining mass spectrometry data are transforming natural products research

Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.

Synthetic Biology Advanced Natural Product Discovery

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a limited number of natural products have been discovered, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels under conventional laboratory conditions. With the rapid development of synthetic biology, advanced genome mining and engineering strategies have been reported and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions.

Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches

Covering: up to the end of 2020Recently introduced computational metabolome mining tools have started to positively impact the chemical and biological interpretation of untargeted metabolomics analyses. We believe that these current advances make it possible to start decomposing complex metabolite mixtures into substructure and chemical class information, thereby supporting pivotal tasks in metabolomics analysis including metabolite annotation, the comparison of metabolic profiles, and network analyses. In this review, we highlight and explain key tools and emerging strategies covering 2015 up to the end of 2020. The majority of these tools aim at processing and analyzing liquid chromatography coupled to mass spectrometry fragmentation data. We start with defining what substructures are, how they relate to molecular fingerprints, and how recognizing them helps to decompose complex mixtures. We continue with chemical classes that are based on the presence or absence of particular molecular scaffolds and/or functional groups and are thus intrinsically related to substructures. We discuss novel tools to mine substructures, annotate chemical compound classes, and create mass spectral networks from metabolomics data and demonstrate them using two case studies. We also review and speculate about the opportunities that NMR spectroscopy-based metabolome mining of complex metabolite mixtures offers to discover substructures and chemical classes. Finally, we will describe the main benefits and limitations of the current tools and strategies that rely on them, and our vision on how this exciting field can develop toward repository-scale-sized metabolomics analyses. Complementary sources of structural information from genomics analyses and well-curated taxonomic records are also discussed. Many research fields such as natural products discovery, pharmacokinetic and drug metabolism studies, and environmental metabolomics increasingly rely on untargeted metabolomics to gain biochemical and biological insights. The here described technical advances will benefit all those metabolomics disciplines by transforming spectral data into knowledge that can answer biological questions.

Probing the Therapeutic Potential of Marine Phyla by SPE Extraction

The marine environment is potentially a prolific source of small molecules with significant biological activities. In recent years, the development of new chromatographic phases and the progress in cell and molecular techniques have facilitated the search for marine natural products (MNPs) as novel pharmacophores and enhanced the success rate in the selection of new potential drug candidates. However, most of this exploration has so far been driven by anticancer research and has been limited to a reduced number of taxonomic groups. In this article, we report a test study on the screening potential of an in-house library of natural small molecules composed of 285 samples derived from 57 marine organisms that were chosen from among the major eukaryotic phyla so far represented in studies on bioactive MNPs. Both the extracts and SPE fractions of these organisms were simultaneously submitted to three different bioassays—two phenotypic and one enzymatic—for cytotoxic, antidiabetic, and antibacterial activity. On the whole, the screening of the MNP library selected 11 potential hits, but the distribution of the biological results showed that SPE fractionation increased the positive score regardless of the taxonomic group. In many cases, activity could be detected only in the enriched fractions after the elimination of the bulky effect due to salts. On a statistical basis, sponges and molluscs were confirmed to be the most significant source of cytotoxic and antimicrobial products, but other phyla were found to be effective with the other therapeutic targets.

A Treasure of Bioactive Compounds from the Deep Sea

The deep-sea environment is a unique, challenging extreme habitat where species have had to adapt to the absence of light, low levels of oxygen, high pressure and little food. In order to survive such harsh conditions, these organisms have evolved different biochemical and physiological features that often have no other equivalent in terrestrial habitats. Recent analyses have highlighted how the deep sea is one of the most diverse and species-rich habitats on the planet but less explored compared to more accessible sites. Because of their adaptation to this extreme environment, deep-sea species have the potential to produce novel secondary metabolites with potent biological activities. Recent advances in sampling and novel techniques in microorganism culturing and chemical isolation have promoted the discovery of bioactive agents from deep-sea organisms. However, reports of natural products derived from deep-sea species are still scarce, probably because of the difficulty in accessing deep-sea samples, sampling costs and the difficulty in culturing deep-sea organisms. In this review, we give an overview of the potential treasure represented by metabolites produced by deep marine species and their bioactivities for the treatment and prevention of various human pathologies.

Marine Biodiscovery in a Changing World

The term "marine biodiscovery" has been recently been adopted to describe the area of marine natural products dedicated to the search of new drugs. Several maritime countries such as Australia, New Zealand, South Korea, and Japan as well as some European countries have invested significantly in this area of research over the last 50 years. In the late 2000s, research in this field has received significant interest and support in Ireland for exploring new marine bioresources from the nutrient-rich waters of the Northeastern Atlantic Ocean. Despite undeniable success exemplified by the marketing of new drugs, especially in oncology, the integration of new technical but also environmental aspects should be considered. Indeed, global change, particularly in our oceans, such as climate change, biodiversity loss, and the emergence of microbial pathogens, not only affects the environment but ultimately contributes to social inequalities. In this contribution, new avenues and best practices are proposed, such as the development of biorepositories and shared data for the future of marine biodiscovery research. The extension of this type of scientific work will allow humanity to finally make the optimum use of marine bioresources.

Metagenomic Sequencing of Multiple Soil Horizons and Sites in Close Vicinity Revealed Novel Secondary Metabolite Diversity

Discovery of novel antibiotics is crucial for combating rapidly spreading antimicrobial resistance and new infectious diseases. Most of the clinically used antibiotics are natural products—secondary metabolites produced by soil microbes that can be cultured in the lab. Rediscovery of these secondary metabolites during discovery expeditions costs both time and resources. Metagenomics approaches can overcome this challenge by capturing both culturable and unculturable hidden microbial diversity. To be effective, such an approach should address questions like the following. Which sequencing method is better at capturing the microbial diversity and biosynthesis potential? What part of the soil should be sampled? Can patterns and correlations from such big-data explorations guide future novel natural product discovery surveys? Here, we address these questions by a paired amplicon and shotgun metagenomic sequencing survey of samples from soil horizons of multiple forest sites very close to each other. Metagenome mining identified numerous novel biosynthetic gene clusters (BGCs) and enzymatic domain sequences. Hybrid assembly of both long reads and short reads improved the metagenomic assembly and resulted in better BGC annotations. A higher percentage of novel domains was recovered from shotgun metagenome data sets than from amplicon data sets. Overall, in addition to revealing the biosynthetic potential of soil microbes, our results suggest the importance of sampling not only different soils but also their horizons to capture microbial and biosynthetic diversity and highlight the merits of metagenome sequencing methods.

IMPORTANCE This study helped uncover the biosynthesis potential of forest soils via exploration of shotgun metagenome and amplicon sequencing methods and showed that both methods are needed to expose the full microbial diversity in soil. Based on our metagenome mining results, we suggest revising the historical strategy of sampling soils from far-flung places, as we found a significant number of novel and diverse BGCs and domains even in different soils that are very close to each other. Furthermore, sampling of different soil horizons can reveal the additional diversity that often remains hidden and is mainly caused by differences in environmental key parameters such as soil pH and nutrient content. This paired metagenomic survey identified diversity patterns and correlations, a step toward developing a rational approach for future natural product discovery surveys.

iCYP-MFE: Identifying Human Cytochrome P450 Inhibitors Using Multitask Learning and Molecular Fingerprint-Embedded Encoding

The human cytochrome P450 (CYP) superfamily holds responsibilities for the metabolism of both endogenous and exogenous compounds such as drugs, cellular metabolites, and toxins. The inhibition exerted on the CYP enzymes is closely associated with adverse drug reactions encompassing metabolic failures and induced side effects. In modern drug discovery, identification of potential CYP inhibitors is, therefore, highly essential. Alongside experimental approaches, numerous computational models have been proposed to address this biochemical issue. In this study, we introduce iCYP-MFE, a computational framework for virtual screening on CYP inhibitors toward 1A2, 2C9, 2C19, 2D6, and 3A4 isoforms. iCYP-MFE contains a set of five robust, stable, and effective prediction models developed using multitask learning incorporated with molecular fingerprint-embedded features. The results show that multitask learning can remarkably leverage useful information from related tasks to promote global performance. Comparative analysis indicates that iCYP-MFE achieves three predominant tasks, one equivalent task, and one less effective task compared to state-of-the-art methods. The area under the receiver operating characteristic curve (AUC-ROC) and the area under the precision-recall curve (AUC-PR) were two decisive metrics used for model evaluation. The prediction task for CYP2D6-inhibition achieves the highest AUC-ROC value of 0.93 while the prediction task for CYP1A2-inhibition obtains the highest AUC-PR value of 0.92. The substructural analysis preliminarily explains the nature of the CYP-inhibitory activity of compounds. An online web server for iCYP-MFE with a user-friendly interface was also deployed to support scientific communities in identifying CYP inhibitors.

Streptomyces: connecting red-nano and grey biotechnology fields

Anthropogenic activities are often related to the occurrence of simultaneous contaminations with heavy metals and toxic organic compounds. In addition, the increasing demand for food, clothing, and technology has increased the worldwide contamination level. Although it is not fully demonstrated, the high level of contamination in association with the indiscriminate use of antibiotics, led to the appearance of multi-resistant pathogenic microorganisms. Grey and red biotechnologies try to counteract the negative effects of pollution and antimicrobial resistance respectively. Streptomyces is well known in the field of biotechnology. In this review, we discussed the potential of these bacteria to deal with organic and inorganic pollutants and produce nanostructures with antimicrobial activity. To our knowledge, this is the first work in which a biotechnological bacterial genus such as Streptomyces is revised in two different fields of global concern, contamination, and multi-drugs resistant microorganisms.

Metabolomics for Crop Breeding: General Considerations

The development of new, more productive varieties of agricultural crops is becoming an increasingly difficult task. Modern approaches for the identification of beneficial alleles and their use in elite cultivars, such as quantitative trait loci (QTL) mapping and marker-assisted selection (MAS), are effective but insufficient for keeping pace with the improvement of wheat or other crops. Metabolomics is a powerful but underutilized approach that can assist crop breeding. In this review, basic methodological information is summarized, and the current strategies of applications of metabolomics related to crop breeding are explored using recent examples. We briefly describe classes of plant metabolites, cellular localization of metabolic pathways, and the strengths and weaknesses of the main metabolomics technique. Among the commercialized genetically modified crops, about 50 with altered metabolic enzyme activities have been identified in the International Service for the Acquisition of Agri-biotech Applications (ISAAA) database. These plants are reviewed as encouraging examples of the application of knowledge of biochemical pathways. Based on the recent examples of metabolomic studies, we discuss the performance of metabolic markers, the integration of metabolic and genomic data in metabolic QTLs (mQTLs) and metabolic genome-wide association studies (mGWAS). The elucidation of metabolic pathways and involved genes will help in crop breeding and the introgression of alleles of wild relatives in a more targeted manner.

Investigation on the Phytochemical Composition, Antioxidant and Enzyme Inhibition Potential of Polygonum Plebeium R.Br: A Comprehensive Approach to Disclose New Nutraceutical and Functional Food Ingredients

The present work describes medicinal potential and secondary metabolic picture of the methanol extract (PP-M) of Polygonum plebeium R.Br. and its fractions; hexane (PP-H), ethyl acetate (PP-E) and water (PP-W). In total bioactive component estimation, highest contents of phenolic (89.38±0.27 mgGAE/g extract) and flavonoid (51.21±0.43 mgQE/g extract) were observed in PP-E, and the same fraction exhibited the highest antioxidant potential in DPPH (324.80±4.09 mgTE/g extract), ABTS (563.18±11.39 mgTE/g extract), CUPRAC (411.33±15.49 mgTE/g extract) and FRAC (369.54±1.70 mgTE/g extract) assays. In Phosphomolybdenum activity assay, PP-H and PP-E showed nearly similar potential, however, PP-H was the most active (13.54±0.24 mgEDTAE/g extract) in metal chelating activity assay. PP-W was the stronger inhibitor (4.03±0.05 mgGALAE/g extract) of the enzyme AChE, while PP-H was potent inhibitor of BChE (5.62±0.27 mg GALAE/g extract). Interestingly, PP-E was inactive against BChE. Against tyrosinase activity, PP-E was again the most active fraction with inhibitory value of 71.89±1.44 mg KAE/g extract, followed by the activity of PP-M and PP-W. Antidiabetic potential was almost equally distributed among PP-M, PP-H and PP-E. For mapping the chemodiversity of P. plebeium, PP-M was analyzed through UHPLC/MS, which led to the identification of more than 50 compounds. Flavonoids were the main components derived from isovitexin, kaempferol and luteolin however, gallic acid, protocatechuic acid, gingerols and lyoniresinol 9'-sulfate were among important bioactive phenols. These findings prompted to conclude that Polygonum plebeium can be a significant source to offer new ingredient for nutraceuticals and functional foods.

Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop

We report the major conclusions of the online open-access workshop "Computational Applications in Secondary Metabolite Discovery (CAiSMD)" that took place from 08 to 10 March 2021. Invited speakers from academia and industry and about 200 registered participants from five continents (Africa, Asia, Europe, South America, and North America) took part in the workshop. The workshop highlighted the potential applications of computational methodologies in the search for secondary metabolites (SMs) or natural products (NPs) as potential drugs and drug leads. During 3 days, the participants of this online workshop received an overview of modern computer-based approaches for exploring NP discovery in the "omics" age. The invited experts gave keynote lectures, trained participants in hands-on sessions, and held round table discussions. This was followed by oral presentations with much interaction between the speakers and the audience. Selected applicants (early-career scientists) were offered the opportunity to give oral presentations (15 min) and present posters in the form of flash presentations (5 min) upon submission of an abstract. The final program available on the workshop website ( https://caismd.indiayouth.info/ ) comprised of 4 keynote lectures (KLs), 12 oral presentations (OPs), 2 round table discussions (RTDs), and 5 hands-on sessions (HSs). This meeting report also references internet resources for computational biology in the area of secondary metabolites that are of use outside of the workshop areas and will constitute a long-term valuable source for the community. The workshop concluded with an online survey form to be completed by speakers and participants for the goal of improving any subsequent editions.

Phytochemicals: A Promising Weapon in the Arsenal against Antibiotic-Resistant Bacteria

The extensive usage of antibiotics and the rapid emergence of antimicrobial-resistant microbes (AMR) are becoming important global public health issues. Many solutions to these problems have been proposed, including developing alternative compounds with antimicrobial activities, managing existing antimicrobials, and rapidly detecting AMR pathogens. Among all of them, employing alternative compounds such as phytochemicals alone or in combination with other antibacterial agents appears to be both an effective and safe strategy for battling against these pathogens. The present review summarizes the scientific evidence on the biochemical, pharmacological, and clinical aspects of phytochemicals used to treat microbial pathogenesis. A wide range of commercial products are currently available on the market. Their well-documented clinical efficacy suggests that phytomedicines are valuable sources of new types of antimicrobial agents for future use. Innovative approaches and methodologies for identifying plant-derived products effective against AMR are also proposed in this review.

Towards the sustainable discovery and development of new antibiotics

An ever-increasing demand for novel antimicrobials to treat life-threatening infections caused by the global spread of multidrug-resistant bacterial pathogens stands in stark contrast to the current level of investment in their development, particularly in the fields of natural-product-derived and synthetic small molecules. New agents displaying innovative chemistry and modes of action are desperately needed worldwide to tackle the public health menace posed by antimicrobial resistance. Here, our consortium presents a strategic blueprint to substantially improve our ability to discover and develop new antibiotics. We propose both short-term and long-term solutions to overcome the most urgent limitations in the various sectors of research and funding, aiming to bridge the gap between academic, industrial and political stakeholders, and to unite interdisciplinary expertise in order to efficiently fuel the translational pipeline for the benefit of future generations.

Small Molecules of Natural Origin as Potential Anti-HIV Agents: A Computational Approach

The human immunodeficiency virus type 1 (HIV-1), one of the leading causes of infectious death globally, generates severe damages to people's immune systems and makes them susceptible to serious diseases. To date, there are no drugs that completely remove HIV from the body. This paper focuses on screening 224,205 natural compounds of ZINC15 NPs subset to identify those with bioactivity similar to non-nucleoside reverse transcriptase inhibitors (NNRTIs) as promising candidates to treat HIV-1. To reach the goal, an in silico approach involving 3D-similarity search, ADMETox, HIV protein-inhibitor prediction, docking, and MM-GBSA free-binding energies was trained. The FDA-approved HIV drugs, efavirenz, etravirine, rilpivirine, and doravirine, were used as queries. The prioritized compounds were subjected to ADMETox, docking, and MM-GBSA studies against HIV-1 reverse transcriptase (RT). Lys101, Tyr181, Tyr188, Trp229, and Tyr318 residues and free-binding energies have proved that ligands can stably bind to HIV-1 RT. Three natural products (ZINC37538901, ZINC38321654, and ZINC67912677) containing oxan and oxolan rings with hydroxyl substituents and one (ZINC2103242) having 3,6,7,8-tetrahydro-2H-pyrido[1,2-a]pyrazine-1,4-dione core exhibited comparable profiles to etravirine and doravirine, with ZINC2103242 being the most promising anti-HIV candidate in terms of drug metabolism and safety profile. These findings may open new avenues to guide the rational design of novel HIV-1 NNRTIs.

Metabolomic Characterization of a cf. Neolyngbya Cyanobacterium from the South China Sea Reveals Wenchangamide A, a Lipopeptide with In Vitro Apoptotic Potential in Colon Cancer Cells

Metabolomics can be used to study complex mixtures of natural products, or secondary metabolites, for many different purposes. One productive application of metabolomics that has emerged in recent years is the guiding direction for isolating molecules with structural novelty through analysis of untargeted LC-MS/MS data. The metabolomics-driven investigation and bioassay-guided fractionation of a biomass assemblage from the South China Sea dominated by a marine filamentous cyanobacteria, cf. Neolyngbya sp., has led to the discovery of a natural product in this study, wenchangamide A (1). Wenchangamide A was found to concentration-dependently cause fast-onset apoptosis in HCT116 human colon cancer cells in vitro (24 h IC₅₀ = 38 μM). Untargeted metabolomics, by way of MS/MS molecular networking, was used further to generate a structural proposal for a new natural product analogue of 1, here coined wenchangamide B, which was present in the organic extract and bioactive sub-fractions of the biomass examined. The wenchangamides are of interest for anticancer drug discovery, and the characterization of these molecules will facilitate the future discovery of related natural products and development of synthetic analogues.

Isolation and characterization of marine sponge-associated Streptomyces sp. NMF6 strain producing secondary metabolite(s) possessing antimicrobial, antioxidant, anticancer, and antiviral activities

Background

Actinomycetes associated with marine sponge represent a promising source of bioactive compounds. Herein, we report the isolation, identification, and bioactivity evaluation of Streptomyces sp. NMF6 associated with the marine sponge Diacarnus ardoukobae.

Results

Results showed that the strain belonged to the genus Streptomyces, and it was designated as Streptomyces sp. NMF6 with the GenBank accession number MW015111. Ethyl acetate (EtOAc) extract of the strain NMF6 demonstrated a promising antimicrobial activity against Staphylococcus aureus, Enterococcus faecalis, Vibrio damsela, and Candida albicans and a strong antioxidant activity, which were confirmed by DPPH, ferric-reducing power, and phosphomolybdenum assays; results are expressed as ascorbic acid equivalents. NMF6 extract also demonstrated cytotoxicity against breast cancer cell line (MCF-7), hepatocellular carcinoma cell line (Hep-G2), and human colon carcinoma cell line (HCT-116); the selectivity index values were < 2. The extract showed promising antiviral activity against HSV-1, CoxB4, and hepatitis A viruses at concentrations that were nontoxic to the host cells, with the selectivity index values being 13.25, 9.42, and 8.25, respectively. GC-MS analysis of the extract showed the presence of 20 compounds, with bis(2-ethylhexyl) phthalate being the major component (48%).

Conclusions

Our study indicates that the marine sponge–associated Streptomyces sp. NMF6 strain is a potential source of bioactive compounds that could be developed into therapeutic agents.

Taxonomy-Focused Natural Product Databases for Carbon-13 NMR-Based Dereplication

The recent revival of the study of organic natural products as renewable sources of medicinal drugs, cosmetics, dyes, and materials motivated the creation of general purpose structural databases. Dereplication, the efficient identification of already reported compounds, relies on the grouping of structural, taxonomic and spectroscopic databases that focus on a particular taxon (species, genus, family, order, etc.). A set of freely available python scripts, CNMR_Predict, is proposed for the quick supplementation of taxon oriented search results from the naturaL prOducTs occUrrences database (LOTUS, lotus.naturalproducts.net) with predicted carbon-13 nuclear magnetic resonance data from the ACD/Labs CNMR predictor and DB software (acdlabs.com) to provide easily searchable databases. The database construction process is illustrated using Brassica rapa as a taxon example.

NP Navigator: A New Look at the Natural Product Chemical Space

Natural products (NPs), being evolutionary selected over millions of years to bind to biological macromolecules, remained an important source of inspiration for medicinal chemists even after the advent of efficient drug discovery technologies such as combinatorial chemistry and high-throughput screening. Thus, there is a strong demand for efficient and user-friendly computational tools that allow to analyze large libraries of NPs. In this context, we introduce NP Navigator - a freely available intuitive online tool for visualization and navigation through the chemical space of NPs and NP-like molecules. It is based on the hierarchical ensemble of generative topographic maps, featuring NPs from the COlleCtion of Open NatUral producTs (COCONUT), bioactive compounds from ChEMBL and commercially available molecules from ZINC. NP Navigator allows to efficiently analyze different aspects of NPs - chemotype distribution, physicochemical properties, biological activity and commercial availability of NPs. The latter concerns not only purchasable NPs but also their close analogs that can be considered as synthetic mimetics of NPs or pseudo-NPs.

Chemical Space, Scaffolds, and Halogenated Compounds of CMNPD: A Comprehensive Chemoinformatic Analysis

The comprehensive marine natural products database (CMNPD) is a new free access and comprehensive database developed originally by Lyu's team of our research group, including more than 30 000 marine natural products (MNPs) reported from the 1960s. In this article, we aimed to present CMNPD's value in drug discovery and to present several characteristics of MNPs based on our new comprehensive data. We used chemoinformatic analysis methods to report the molecular properties, chemical space, and several scaffold assessments of CMNPD compared with several databases. Then, we reported the characteristics of MNPs from the aspect of halogens, comparing MNPs with terrestrial natural products (TNPs) and drugs. We found that CMNPD had a low proportion (2.91%) of scaffolds utilized by drugs, and high similarities between CMNPD and NPAtlas (a microbial natural products database), which are worth further investigation. The proportion of bromides in MNPs is outstandingly higher (11.0%) in contrast to other halogens. Furthermore, the results showed great differences in halogenated structures between MNPs and drugs, especially brominated substructures. Finally, we found that many marine species (2.52%) reported only halogenated compounds. It can be concluded from these results that CMNPD is a promising source for drug discovery and has many scientific issues relative to MNPs that need to be further investigated.

Alkaloids in Contemporary Drug Discovery to Meet Global Disease Needs

An overview is presented of the well-established role of alkaloids in drug discovery, the application of more sustainable chemicals, and biological approaches, and the implementation of information systems to address the current challenges faced in meeting global disease needs. The necessity for a new international paradigm for natural product discovery and development for the treatment of multidrug resistant organisms, and rare and neglected tropical diseases in the era of the Fourth Industrial Revolution and the Quintuple Helix is discussed.

Metabolomics as a Tool to Study Underused Soy Parts: In Search of Bioactive Compounds

The valorization of agri-food by-products is essential from both economic and sustainability perspectives. The large quantity of such materials causes problems for the environment; however, they can also generate new valuable ingredients and products which promote beneficial effects on human health. It is estimated that soybean production, the major oilseed crop worldwide, will leave about 597 million metric tons of branches, leaves, pods, and roots on the ground post-harvesting in 2020/21. An alternative for the use of soy-related by-products arises from the several bioactive compounds found in this plant. Metabolomics studies have already identified isoflavonoids, saponins, and organic and fatty acids, among other metabolites, in all soy organs. The present review aims to show the application of metabolomics for identifying high-added-value compounds in underused parts of the soy plant, listing the main bioactive metabolites identified up to now, as well as the factors affecting their production.

The SistematX Web Portal of Natural Products: An Update

Natural products and their secondary metabolites are promising starting points for the development of drug prototypes and new drugs, as many current treatments for numerous diseases are directly or indirectly related to such compounds. State-of-the-art, curated, integrated, and frequently updated databases of secondary metabolites are thus highly relevant to drug discovery. The SistematX Web Portal, introduced in 2018, is undergoing development to address this need and documents crucial information about plant secondary metabolites, including the exact location of the species from which the compounds were isolated. SistematX also allows registered users to log in to the data management area and gain access to administrative pages. This study reports recent updates and modifications to the SistematX Web Portal, including a batch download option, the generation and visualization of ¹H and ¹³C nuclear magnetic resonance spectra, and the calculation of physicochemical (drug-like and lead-like) properties and biological activity profiles. The SistematX Web Portal is freely available at http://sistematx.ufpb.br.

CyanoMetDB, a comprehensive public database of secondary metabolites from cyanobacteria

Harmful cyanobacterial blooms, which frequently contain toxic secondary metabolites, are reported in aquatic environments around the world. More than two thousand cyanobacterial secondary metabolites have been reported from diverse sources over the past fifty years. A comprehensive, publically-accessible database detailing these secondary metabolites would facilitate research into their occurrence, functions and toxicological risks. To address this need we created CyanoMetDB, a highly curated, flat-file, openly-accessible database of cyanobacterial secondary metabolites collated from 850 peer-reviewed articles published between 1967 and 2020. CyanoMetDB contains 2010 cyanobacterial metabolites and 99 structurally related compounds. This has nearly doubled the number of entries with complete literature metadata and structural composition information compared to previously available open access databases. The dataset includes microcytsins, cyanopeptolins, other depsipeptides, anabaenopeptins, microginins, aeruginosins, cyclamides, cryptophycins, saxitoxins, spumigins, microviridins, and anatoxins among other metabolite classes. A comprehensive database dedicated to cyanobacterial secondary metabolites facilitates: (1) the detection and dereplication of known cyanobacterial toxins and secondary metabolites; (2) the identification of novel natural products from cyanobacteria; (3) research on biosynthesis of cyanobacterial secondary metabolites, including substructure searches; and (4) the investigation of their abundance, persistence, and toxicity in natural environments.

New software tools, databases, and resources in metabolomics: updates from 2020

BACKGROUND

Precision medicine, space exploration, drug discovery to characterization of dark chemical space of habitats and organisms, metabolomics takes a centre stage in providing answers to diverse biological, biomedical, and environmental questions. With technological advances in mass-spectrometry and spectroscopy platforms that aid in generation of information rich datasets that are complex big-data, data analytics tend to co-evolve to match the pace of analytical instrumentation. Software tools, resources, databases, and solutions help in harnessing the concealed information in the generated data for eventual translational success.

AIM OF THE REVIEW

In this review, ~ 85 metabolomics software resources, packages, tools, databases, and other utilities that appeared in 2020 are introduced to the research community.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In Table 1 the computational dependencies and downloadable links of the tools are provided, and the resources are categorized based on their utility. The review aims to keep the community of metabolomics researchers updated with all the resources developed in 2020 at a collated avenue, in line with efforts form 2015 onwards to help them find these at one place for further referencing and use.

Current Advances in the Use of Nanophytomedicine Therapies for Human Cardiovascular Diseases

Considering the high prevalence of cardiovascular diseases (CVDs), the primary cause of death during the last several decades, it is necessary to develop proper strategies for the prevention and treatment of CVDs. Given the excessive side effects of current therapies, alternative therapeutic approaches like medicinal plants and natural products are preferred. Lower toxicity, chemical diversity, cost-effectiveness, and proven therapeutic potentials make natural products superior compared to other products. Nanoformulation methods improve the solubility, bioavailability, circulation time, surface area-to-volume ratio, systemic adverse side effects, and drug delivery efficiency of these medications. This study intended to review the functionality of the most recent nanoformulated medicinal plants and/or natural products against various cardiovascular conditions such as hypertension, atherosclerosis, thrombosis, and myocardial infarction. Literature review revealed that curcumin, quercetin, and resveratrol were the most applied natural products, respectively. Combination therapy, conjugation, or fabrication of nanoparticles and nanocarriers improved the applications and therapeutic efficacy of herbal- or natural-based nanoformulations. In the context of CVDs prevention and/or treatment, available data suggest that natural-based nanoformulations are considerably efficient, alone or in blend with other herbal/synthetic medicines. However, clinical trials are mandatory to elucidate the safety, cardioprotective effect, and mechanism of actions of nanophytomedicines.

Expanding the Chemical Information Science gateway

As chemical information evolves, impacting many chemistry areas, effective ways to disseminate results by the scientific community are also changing. Thus, publication schemes adapt to meet the needs of researchers across disciplines to share high-quality data, information, and knowledge. Since 2015, the F1000Research Chemical Information Science (CIS) gateway has offered an open and unique model to disseminate science at the interface of chemoinformatics, bioinformatics, and several other informatic-related disciplines. In response to the evolution of chemical information science, the F1000Research CIS gateway has incorporated new members to the advisory board. It is also reinforcing and expanding the gateway areas with a particular focus on machine learning and metabolomics. The range of available article types, availability of data, exposure within complementary multidisciplinary F1000Research gateways, and indexing in major bibliographic databases increases the visibility of all contributions. As part of progressing open science in this field, we look forward to your high-quality contributions to the CIS gateway.

The Design-Build-Test-Learn cycle for metabolic engineering of Streptomycetes

Streptomycetes are producers of a wide range of specialized metabolites of great medicinal and industrial importance, such as antibiotics, antifungals, or pesticides. Having been the drivers of the golden age of antibiotics in the 1950s and 1960s, technological advancements over the last two decades have revealed that very little of their biosynthetic potential has been exploited so far. Given the great need for new antibiotics due to the emerging antimicrobial resistance crisis, as well as the urgent need for sustainable biobased production of complex molecules, there is a great renewed interest in exploring and engineering the biosynthetic potential of streptomycetes. Here, we describe the Design-Build-Test-Learn (DBTL) cycle for metabolic engineering experiments in streptomycetes and how it can be used for the discovery and production of novel specialized metabolites.

SANCDB: an update on South African natural compounds and their readily available analogs

BACKGROUND

South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/ ) is the sole and a fully referenced database of natural chemical compounds of South African biodiversity. It is freely available, and since its inception in 2015, the database has become an important resource to several studies. Its content has been: used as training data for machine learning models; incorporated to larger databases; and utilized in drug discovery studies for hit identifications.

DESCRIPTION

Here, we report the updated version of SANCDB. The new version includes 412 additional compounds that have been reported since 2015, giving a total of 1012 compounds in the database. Further, although natural products (NPs) are an important source of unique scaffolds, they have a major drawback due to their complex structure resulting in low synthetic feasibility in the laboratory. With this in mind, SANCDB is, now, updated to provide direct links to commercially available analogs from two major chemical databases namely Mcule and MolPort. To our knowledge, this feature is not available in other NP databases. Additionally, for easier access to information by users, the database and website interface were updated. The compounds are now downloadable in many different chemical formats.

CONCLUSIONS

The drug discovery process relies heavily on NPs due to their unique chemical organization. This has inspired the establishment of numerous NP chemical databases. With the emergence of newer chemoinformatic technologies, existing chemical databases require constant updates to facilitate information accessibility and integration by users. Besides increasing the NPs compound content, the updated SANCDB allows users to access the individual compounds (if available) or their analogs from commercial databases seamlessly.

Latin American databases of natural products: biodiversity and drug discovery against SARS-CoV-2

In this study, we evaluated 3444 Latin American natural products using cheminformatic tools. We also characterized 196 compounds for the first time from the flora of El Salvador that were compared with the databases of secondary metabolites from Brazil, Mexico, and Panama, and 42 969 compounds (natural, semi-synthetic, synthetic) from different regions of the world. The overall analysis was performed using drug-likeness properties, molecular fingerprints of different designs, two parameters similarity, molecular scaffolds, and molecular complexity metrics. It was found that, in general, Salvadoran natural products have a large diversity based on fingerprints. Simultaneously, those belonging to Mexico and Panama present the greatest diversity of scaffolds compared to the other databases. This study provided evidence of the high structural complexity that Latin America's natural products have as a benchmark. The COVID-19 pandemic has had a negative effect on a global level. Thus, in the search for substances that may influence the coronavirus life cycle, the secondary metabolites from El Salvador and Panama were evaluated by docking against the endoribonuclease NSP-15, an enzyme involved in the SARS CoV-2 viral replication. We propose in this study three natural products as potential inhibitors of NSP-15.

Novel Compounds Targeting Neuropilin Receptor 1 with Potential To Interfere with SARS-CoV-2 Virus Entry

Neuropilin-1 (NRP-1) is a multifunctional transmembrane receptor for ligands that affect developmental axonal growth and angiogenesis. In addition to a role in cancer, NRP-1 is a reported entry point for several viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19). The furin cleavage product of SARS-CoV-2 Spike protein takes advantage of the vascular endothelial growth factor A (VEGF-A) binding site on NRP-1 which accommodates a polybasic stretch ending in a C-terminal arginine. This site has long been a focus of drug discovery efforts for cancer therapeutics. We recently showed that interruption of the VEGF-A/NRP-1 signaling pathway ameliorates neuropathic pain and hypothesize that interference of this pathway by SARS-CoV-2 Spike protein interferes with pain signaling. Here, we report confirmed hits from a small molecule and natural product screen of nearly 0.5 million compounds targeting the VEGF-A binding site on NRP-1. We identified nine chemical series with lead- or drug-like physicochemical properties. Using ELISA, we demonstrate that six compounds disrupt VEGF-A-NRP-1 binding more effectively than EG00229, a known NRP-1 inhibitor. Secondary validation in cells revealed that all tested compounds inhibited VEGF-A triggered VEGFR2 phosphorylation. Further, two compounds displayed robust inhibition of a recombinant vesicular stomatitis virus protein that utilizes the SARS-CoV-2 Spike for entry and fusion. These compounds represent a first step in a renewed effort to develop small molecule inhibitors of the VEGF-A/NRP-1 signaling for the treatment of neuropathic pain and cancer with the added potential of inhibiting SARS-CoV-2 virus entry.

An Integrated Strategy for the Detection, Dereplication, and Identification of DNA-Binding Biomolecules from Complex Natural Product Mixtures

A fundamental factor in natural product drug discovery programs is the necessity to identify the active component(s) from complex chemical mixtures. Whereas this has traditionally been accomplished using bioassay-guided fractionation, we questioned whether alternative techniques could supplement and, in some cases, even supplant this approach. We speculated that a combination of ligand-fishing methods and modern analytical tools (e.g., LC-MS and online natural product databases) offered a route to enhance natural product drug discovery. Herein, a candidate solution referred to as the lickety-split ligand-affinity-based molecular angling system (LLAMAS) is described. This approach utilizes an ultrafiltration-based LC-PDA-MS/MS-guided DNA-binding assay in combination with the (i) Global Natural Products Social Molecular Networking, (ii) Dictionary of Natural Products, and (iii) SciFinder platforms to identify DNA binders in complex chemical mixtures. LLAMAS was initially vetted in tests using known small-molecule DNA binders and then optimized to a 96-well plate-based format. A set of 332 plant samples used in traditional Chinese medicine was screened for DNA-binding activity with LLAMAS, resulting in the identification of seven DNA-binding molecules, including berberine (12), palmatine (13), coptisine (14), fangchinoline (15), tetrandrine (16), daurisoline (17), and dauricine (18). These results demonstrate that LLAMAS is an effective natural product discovery platform for the efficient identification and dereplication of DNA-binding molecules from complex mixtures.

Description and Analysis of Glycosidic Residues in the Largest Open Natural Products Database

Natural products (NPs), biomolecules produced by living organisms, inspire the pharmaceutical industry and research due to their structural characteristics and the substituents from which they derive their activities. Glycosidic residues are frequently present in NP structures and have particular pharmacokinetic and pharmacodynamic importance as they improve their solubility and are often involved in molecular transport, target specificity, ligand–target interactions, and receptor binding. The COlleCtion of Open Natural prodUcTs (COCONUT) is currently the largest open database of NPs, and therefore a suitable starting point for the detection and analysis of the diversity of glycosidic residues in NPs. In this work, we report and describe the presence of circular, linear, terminal, and non-terminal glycosidic units in NPs, together with their importance in drug discovery.

Natural products in drug discovery: advances and opportunities

Natural products and their structural analogues have historically made a major contribution to pharmacotherapy, especially for cancer and infectious diseases. Nevertheless, natural products also present challenges for drug discovery, such as technical barriers to screening, isolation, characterization and optimization, which contributed to a decline in their pursuit by the pharmaceutical industry from the 1990s onwards. In recent years, several technological and scientific developments - including improved analytical tools, genome mining and engineering strategies, and microbial culturing advances - are addressing such challenges and opening up new opportunities. Consequently, interest in natural products as drug leads is being revitalized, particularly for tackling antimicrobial resistance. Here, we summarize recent technological developments that are enabling natural product-based drug discovery, highlight selected applications and discuss key opportunities.

Natural Products, the Fourth Industrial Revolution, and the Quintuple Helix

The profound interconnectedness of the sciences and technologies embodied in the Fourth Industrial Revolution is discussed in terms of the global role of natural products, and how that interplays with the development of sustainable and climate-conscious practices of cyberecoethnopharmacolomics within the Quintuple Helix for the promotion of a healthier planet and society.

PSC-db: A Structured and Searchable 3D-Database for Plant Secondary Compounds

Plants synthesize a large number of natural products, many of which are bioactive and have practical values as well as commercial potential. To explore this vast structural diversity, we present PSC-db, a unique plant metabolite database aimed to categorize the diverse phytochemical space by providing 3D-structural information along with physicochemical and pharmaceutical properties of the most relevant natural products. PSC-db may be utilized, for example, in qualitative estimation of biological activities (Quantitative Structure-Activity Relationship, QSAR) or massive docking campaigns to identify new bioactive compounds, as well as potential binding sites in target proteins. PSC-db has been implemented using the open-source PostgreSQL database platform where all compounds with their complementary and calculated information (classification, redundant names, unique IDs, physicochemical properties, etc.) were hierarchically organized. The source organism for each compound, as well as its biological activities against protein targets, cell lines and different organism were also included. PSC-db is freely available for public use and is hosted at the Universidad de Talca.

Discovery of Alternative Chemotherapy Options for Leishmaniasis through Computational Studies of Asteraceae

Leishmaniasis is a complex disease caused by over 20 Leishmania species that primarily affects populations with poor socioeconomic conditions. Currently available drugs for treating leishmaniasis include amphotericin B, paromomycin, and pentavalent antimonials, which have been associated with several limitations, such as low efficacy, the development of drug resistance, and high toxicity. Natural products are an interesting source of new drug candidates. The Asteraceae family includes more than 23 000 species worldwide. Secondary metabolites that can be found in species from this family have been widely explored as potential new treatments for leishmaniasis. Recently, computational tools have become more popular in medicinal chemistry to establish experimental designs, identify new drugs, and compare the molecular structures and activities of novel compounds. Herein, we review various studies that have used computational tools to examine various compounds identified in the Asteraceae family in the search for potential drug candidates against Leishmania.

Antiviral drug discovery: preparing for the next pandemic

Clinically approved antiviral drugs are currently available for only 10 of the more than 220 viruses known to infect humans. The SARS-CoV-2 outbreak has exposed the critical need for compounds that can be rapidly mobilised for the treatment of re-emerging or emerging viral diseases, while vaccine development is underway. We review the current status of antiviral therapies focusing on RNA viruses, highlighting strategies for antiviral drug discovery and discuss the challenges, solutions and options to accelerate drug discovery efforts.

The Three Pillars of Natural Product Dereplication. Alkaloids from the Bulbs of Urceolina peruviana (C. Presl) J.F. Macbr. as a Preliminary Test Case

The role and importance of the identification of natural products are discussed in the perspective of the study of secondary metabolites. The rapid identification of already reported compounds, or structural dereplication, is recognized as a key element in natural product chemistry. The biological taxonomy of metabolite producing organisms, the knowledge of metabolite molecular structures, and the availability of metabolite spectroscopic signatures are considered as the three pillars of structural dereplication. The role and the construction of databases is illustrated by references to the KNApSAcK, UNPD, CSEARCH, and COCONUT databases, and by the importance of calculated taxonomic and spectroscopic data as substitutes for missing or lost original ones. Two NMR-based tools, the PNMRNP database that derives from UNPD, and KnapsackSearch, a database generator that provides taxonomically focused libraries of compounds, are proposed to the community of natural product chemists. The study of the alkaloids from Urceolina peruviana, a plant from the Andes used in traditional medicine for antibacterial and anticancer actions, has given the opportunity to test different approaches to dereplication, favoring the use of publicly available data sources.

Honest nutraceuticals, cosmetics, therapies, and foods (NCTFs): standardization and safety of natural products

With the increasing demand for natural products by the consumer in the marketplace it is necessary to see a proportional increase in behind-the-scenes science to ensure that the ideology of safety and honesty, that is justifiably expected by the wider public, is adequately satisfied. It is of essence to have a fair yet firm governance of nutraceuticals, cosmetics, therapies, and foods. However, with increasing sophistications in adulteration and "claim" loopholes that make it easier for adulterated or counterfeited natural products to be "fudged" to meet the pharmacopeia standards, governance protocols must utilize an "identification and authentication" approach that goes beyond the Pharmacopeia standards to help regulate and transparently communicate natural products in the commercial context. While it is becoming a rat race in keeping commercial natural products honest, modern technology can support authenticators and adequately defeat these challenges.

Diverse Taxonomies for Diverse Chemistries: Enhanced Representation of Natural Product Metabolism in UniProtKB

The UniProt Knowledgebase UniProtKB is a comprehensive, high-quality, and freely accessible resource of protein sequences and functional annotation that covers genomes and proteomes from tens of thousands of taxa, including a broad range of plants and microorganisms producing natural products of medical, nutritional, and agronomical interest. Here we describe work that enhances the utility of UniProtKB as a support for both the study of natural products and for their discovery. The foundation of this work is an improved representation of natural product metabolism in UniProtKB using Rhea, an expert-curated knowledgebase of biochemical reactions, that is built on the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Knowledge of natural products and precursors is captured in ChEBI, enzyme-catalyzed reactions in Rhea, and enzymes in UniProtKB/Swiss-Prot, thereby linking chemical structure data directly to protein knowledge. We provide a practical demonstration of how users can search UniProtKB for protein knowledge relevant to natural products through interactive or programmatic queries using metabolite names and synonyms, chemical identifiers, chemical classes, and chemical structures and show how to federate UniProtKB with other data and knowledge resources and tools using semantic web technologies such as RDF and SPARQL. All UniProtKB data are freely available for download in a broad range of formats for users to further mine or exploit as an annotation source, to enrich other natural product datasets and databases.

COCONUT online: Collection of Open Natural Products database

Natural products (NPs) are small molecules produced by living organisms with potential applications in pharmacology and other industries as many of them are bioactive. This potential raised great interest in NP research around the world and in different application fields, therefore, over the years a multiplication of generalistic and thematic NP databases has been observed. However, there is, at this moment, no online resource regrouping all known NPs in just one place, which would greatly simplify NPs research and allow computational screening and other in silico applications. In this manuscript we present the online version of the COlleCtion of Open Natural prodUcTs (COCONUT): an aggregated dataset of elucidated and predicted NPs collected from open sources and a web interface to browse, search and easily and quickly download NPs. COCONUT web is freely available at https://coconut.naturalproducts.net .

StreptomeDB 3.0: an updated compendium of streptomycetes natural products

Antimicrobial resistance is an emerging global health threat necessitating the rapid development of novel antimicrobials. Remarkably, the vast majority of currently available antibiotics are natural products (NPs) isolated from streptomycetes, soil-dwelling bacteria of the genus Streptomyces. However, there is still a huge reservoir of streptomycetes NPs which remains pharmaceutically untapped and a compendium thereof could serve as a source of inspiration for the rational design of novel antibiotics. Initially released in 2012, StreptomeDB (http://www.pharmbioinf.uni-freiburg.de/streptomedb) is the first and only public online database that enables the interactive phylogenetic exploration of streptomycetes and their isolated or mutasynthesized NPs. In this third release, there are substantial improvements over its forerunners, especially in terms of data content. For instance, about 2500 unique NPs were newly annotated through manual curation of about 1300 PubMed-indexed articles, published in the last five years since the second release. To increase interoperability, StreptomeDB entries were hyperlinked to several spectral, (bio)chemical and chemical vendor databases, and also to a genome-based NP prediction server. Moreover, predicted pharmacokinetic and toxicity profiles were added. Lastly, some recent real-world use cases of StreptomeDB are highlighted, to illustrate its applicability in life sciences.

Microbial natural product databases: moving forward in the multi-omics era

Covering: 2010-2020The digital revolution is driving significant changes in how people store, distribute, and use information. With the advent of new technologies around linked data, machine learning and large-scale network inference, the natural products research field is beginning to embrace real-time sharing and large-scale analysis of digitized experimental data. Databases play a key role in this, as they allow systematic annotation and storage of data for both basic and advanced applications. The quality of the content, structure, and accessibility of these databases all contribute to their usefulness for the scientific community in practice. This review covers the development of databases relevant for microbial natural product discovery during the past decade (2010-2020), including repositories of chemical structures/properties, metabolomics, and genomic data (biosynthetic gene clusters). It provides an overview of the most important databases and their functionalities, highlights some early meta-analyses using such databases, and discusses basic principles to enable widespread interoperability between databases. Furthermore, it points out conceptual and practical challenges in the curation and usage of natural products databases. Finally, the review closes with a discussion of key action points required for the field moving forward, not only for database developers but for any scientist active in the field.

Machine learning approaches for elucidating the biological effects of natural products

Covering: 2000 to 2020 Machine learning (ML) is an efficient tool for the prediction of bioactivity and the study of structure-activity relationships. Over the past decade, an emerging trend for combining these approaches with the study of natural products (NPs) has developed in order to manage the challenge of the discovery of bioactive NPs. In the present review, we will introduce the basic principles and protocols for using the ML approach to investigate the bioactivity of NPs, citing a series of practical examples regarding the study of anti-microbial, anti-cancer, and anti-inflammatory NPs, etc. ML algorithms manage a variety of classification and regression problems associated with bioactive NPs, from those that are linear to non-linear and from pure compounds to plant extracts. Inspired by cases reported in the literature and our own experience, a number of key points have been emphasized for reducing modeling errors, including dataset preparation and applicability domain analysis.