Natural Product Research Research Articles

Editorial Note for Natural Products Chemistry & Research

I am pleased to introduce that the journal of Natural Products Chemistry & Research deals with chemical compounds found in nature that usually has a pharmacological or biological activity for use in pharmaceutical drug discovery and drug design. Natural Products Chemistry & Research emphasizes articles related to the study of chemistry and biochemistry of naturally occurring compounds or the biology of living systems from which they are obtained. Natural Products Journal is at higher echelons that enhance the intelligence and information dissemination on topics closely related to Natural Products. They provide a unique forum dedicated to scientists to express their research articles, review articles, case reports and short communications on an array of Natural Products research. The Natural Products Peer Reviewed Journal is proficiently supported by universally prominent Editorial Board members. Natural Products journal impact factor is mainly calculated based on the number of articles that undergo a double blind peer review process by competent Editorial Board so as to ensure excellence, essence of the work and number of citations received for the same published articles. Abstracts and full texts of all articles published by Natural Products Open Access articles are freely accessible to everyone immediately after publication.

MicroED in natural product and small molecule research.

Covering: 2013 to 2020The electron cryo-microscopy (cryo-EM) method Microcrystal Electron Diffraction (MicroED) allows the collection of high-resolution structural data from vanishingly small crystals that appear like amorphous powders or very fine needles. Since its debut in 2013, data collection and analysis schemes have been fine-tuned, and there are currently close to 100 structures determined by MicroED. Although originally developed to study proteins, MicroED is also very powerful for smaller systems, with some recent and very promising examples from the field of natural products. Herein, we review what has been achieved so far and provide examples of natural product structures, as well as demonstrate the expected future impact of MicroED to the field of natural product and small molecule research.

(DES)CONSTRUINDO A METABOLÔMICA EM PRODUTOS NATURAIS: UM CONVITE A DISCUSSÃO

DECONSTRUCTING METABOLOMICS WITHIN NATURAL PRODUCTS: AN INVITATION FOR A DISCUSSION. The metabolomics approach is widespread and accepted in several lines within life sciences. However, much of what has been called metabolomics could be better defined as a comparison study, regardless of its purpose. Metabolomics finds its definition in the understanding of biological properties and effects on a given organism. In any case, the tools used in metabolomics are undoubtfully useful and should be used in natural products studies, both those already established and those that are under development. Natural products research is in a continuous process of evolution to become a discipline driven by multivariate data with a solid influence of “omic” technologies

Benefiting from big data in natural products: importance of preserving foundational skills and prioritizing data quality.

Systematic, large-scale, studies at the genomic, metabolomic, and functional level have transformed the natural product sciences. Improvements in technology and reduction in cost for obtaining spectroscopic, chromatographic, and genomic data coupled with the creation of readily accessible curated and functionally annotated data sets have altered the practices of virtually all natural product research laboratories. Gone are the days when the natural products researchers were expected to devote themselves exclusively to the isolation, purification, and structure elucidation of small molecules. We now also engage with big data in taxonomic, genomic, proteomic, and/or metabolomic collections, and use these data to generate and test hypotheses. While the oft stated aim for the use of large-scale -omics data in the natural products sciences is to achieve a rapid increase in the rate of discovery of new drugs, this has not yet come to pass. At the same time, new technologies have provided unexpected opportunities for natural products chemists to ask and answer new and different questions. With this viewpoint, we discuss the evolution of big data as a part of natural products research and provide a few examples of how discoveries have been enabled by access to big data. We also draw attention to some of the limitations in our existing engagement with large datasets and consider what would be necessary to overcome them.

Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities.

Covering: 2010 to 2021Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.

Preface

This present volume contains the Proceeding of the 6th International Symposium on Applied Chemistry (ISAC) 2020. In this year, ISAC 2020 is co-organized by Research Center for Chemistry, Research center of Biotechnology, and Research Unit for Natural Product Technology Indonesian Institute of Science (LIPI) which virtually delivered through online event on November 18-20, 2020.By carrying the theme “Natural Medicine and Nutraceutical”, the 6th ISAC 2020 brought together more than 70 presenters and participants from several background such as university lecturer, researcher, and student. With this theme, the symposium brought the latest trends of natural product research in various applications ranging from traditional medicine and pharmaceutical chemistry, pharmaceutical technology and drug delivery system, food technology and nutraceutical, as well as analytical chemistry and chemical engineering. This meeting provides a forum for exchange of information and share of experiences on all aspects of natural medicine and nutraceutical related researches as well as aims to initiate scientific cooperation and international collaboration among the research institutions.List of Advisory Board, Organizing Committee, Technical Program Committee, Scientific Board and Editorial Board are available in this pdf.

The confluence of big data and evolutionary genome mining for the discovery of natural products.

This review covers literature between 2003-2021The development and application of genome mining tools has given rise to ever-growing genetic and chemical databases and propelled natural products research into the modern age of Big Data. Likewise, an explosion of evolutionary studies has unveiled genetic patterns of natural products biosynthesis and function that support Darwin's theory of natural selection and other theories of adaptation and diversification. In this review, we aim to highlight how Big Data and evolutionary thinking converge in the study of natural products, and how this has led to an emerging sub-discipline of evolutionary genome mining of natural products. First, we outline general principles to best utilize Big Data in natural products research, addressing key considerations needed to provide evolutionary context. We then highlight successful examples where Big Data and evolutionary analyses have been combined to provide bioinformatic resources and tools for the discovery of novel natural products and their biosynthetic enzymes. Rather than an exhaustive list of evolution-driven discoveries, we highlight examples where Big Data and evolutionary thinking have been embraced for the evolutionary genome mining of natural products. After reviewing the nascent history of this sub-discipline, we discuss the challenges and opportunities of genomic and metabolomic tools with evolutionary foundations and/or implications and provide a future outlook for this emerging and exciting field of natural product research.

Genome mining methods to discover bioactive natural products.

Covering: 2016 to 2021With genetic information available for hundreds of thousands of organisms in publicly accessible databases, scientists have an unprecedented opportunity to meticulously survey the diversity and inner workings of life. The natural product research community has harnessed this breadth of sequence information to mine microbes, plants, and animals for biosynthetic enzymes capable of producing bioactive compounds. Several orthogonal genome mining strategies have been developed in recent years to target specific chemical features or biological properties of bioactive molecules using biosynthetic, resistance, or transporter proteins. These “biosynthetic hooks” allow researchers to query for biosynthetic gene clusters with a high probability of encoding previously undiscovered, bioactive compounds. This review highlights recent case studies that feature orthogonal approaches that exploit genomic information to specifically discover bioactive natural products and their gene clusters.

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.

Iridium-Catalyzed Asymmetric Hydrogenation of Sterically Hindered Cyclic Imines for Enantioselective Synthesis of Tetrahydroisoquinolines.

An efficient enantioselective hydrogenation of sterically hindered cyclic imines catalyzed by the Ir-tBu-ax-Josiphos complex has been described, producing a series of useful chiral bulky tetrahydroisoquinoline analogs in high isolated yields (85-96%) with good to excellent enantioselectivities (74-99% ee). This transformation provided highly straightforward access to the useful derivatives of tetrahydroisoquinolines, which are of great potential value in drug molecule and natural product research.

Targeted Isolation of Anti-Trypanosomal Naphthofuran-Quinone Compounds from the Mangrove Plant Avicennia lanata.

The discovery of new secondary metabolites from natural origins has become more challenging in natural products research. Different approaches have been applied to target the isolation of new bioactive metabolites from plant extracts. In this study, bioactive natural products were isolated from the crude organic extract of the mangrove plant Avicennia lanata collected from the east coast of Peninsular Malaysia in the Setiu Wetlands, Terengganu, using HRESI-LCMS-based metabolomics-guided isolation and fractionation. Isolation work on the crude extract A. lanata used high-throughput chromatographic techniques to give two new naphthofuranquinone derivatives, hydroxyavicenol C (1) and glycosemiquinone (2), along with the known compounds avicenol C (3), avicequinone C (4), glycoquinone (5), taraxerone (6), taraxerol (7), β-sitosterol (8) and stigmasterol (9). The elucidation and identification of the targeted bioactive compounds used 1D and 2D-NMR and mass spectrometry. Except for 6–9, all isolated naphthoquinone compounds (1–5) from the mangrove plant A. lanata showed significant anti-trypanosomal activity on Trypanosoma brucei brucei with MIC values of 3.12–12.5 μM. Preliminary cytotoxicity screening against normal prostate cells (PNT2A) was also performed. All compounds exhibited low cytotoxicity, with compounds 3 and 4 showing moderate cytotoxicity of 78.3% and 68.6% of the control values at 100 μg/mL, respectively.

Sustainable Low-Volume Analysis of Environmental Samples by Semi-Automated Prioritization of Extracts for Natural Product Research (SeaPEPR).

The discovery of novel natural products (NPs) that will serve as lead structures has to be an ongoing effort to fill the respective development pipelines. However, identification of NPs, which possess a potential for application in e.g., the pharma or agro sector, must be as cost effective and fast as possible. Furthermore, the amount of sample available for initial testing is usually very limited, not least because of the fact that the impact on the environment, i.e., the sampled biosystem, should be kept minimal. Here, our pipeline SeaPEPR is described, in which a primary bioactivity screening of crude extracts is combined with the analysis of their metabolic fingerprint. This enabled prioritization of samples for subsequent microfractionation and dereplication of the active compounds early in the workflow. As a case study, 76 marine sponge-derived extracts were screened against a microbial screening panel. Thereunder, human pathogenic bacteria (Escherichia coli ATCC35218 and Staphylococcus aureus ATCC33592) and yeast (Candida albicans FH2173), as well as the phytopathogenic fungus Septoria tritici MUCL45407. Overall, nine extracts revealed activity against at least one test organism. Metabolic fingerprinting enabled assigning four active extracts into one metabolic group; therefore, one representative was selected for subsequent microfractionation. Dereplication of the active fractions showed a new dibrominated aplysinopsin and a hypothetical chromazonarol stereoisomer derivative. Furthermore, inhibitory activity against the common plant pest Septoria tritici was discovered for NPs of marine origin.

LC-HRMS and acetylcholinesterase affinity assay as a workflow for profiling alkaloids in Annona salzmannii extract

Structure-based molecular networking is useful as a dereplication strategy to identify known molecules, unknown close analogues, or compound families. On the other hand, the ligand fishing assay is a remarkable alternative to accelerate the screening process and to overcome the drawbacks of laborious experiments usually adopted in natural product research. The combination of these approaches contributes to high productivity in disclosing active metabolites and a decrease in lead time identification. To provide a valuable data base for the alkaloids of A. salzmannii bark herein we disclose thirty-one isoquinoline alkaloids including benzyltetrahydroisoquinolines, aporphines, proaporphines, and protoberberines. Among these, twenty-six have not been described for A. salzmannii including the unprecedented alkaloid N,O-dimethylcoclaurine N-oxide. In addition, norcoclaurine (1), norreticuline (13), N,O-dimethylcoclaurine N-oxide (15), and N-acetylasimilobine (24) are now reported for the first time as ligand for acetylcholinesterase.

Development of an innovative maceration technique to optimize extraction and phase partition of natural products

The active component extraction from plants is the first crucial step in natural product research. For non-targeted extraction with an objective to isolate and characterize as many compounds as possible, the most classical technique, and the simplest to implement, is the Soxhlet extraction; however, it does not allow retrieving all the compounds from the plant (when it does not additionally cause artifacts during long heating process). The second most used technique is the extraction by successive macerations using solvents of increasing polarity. While this method is frequently used, few studies are available to rationalize and optimize it. Furthermore, this extraction technique requires some enhancement mainly for efficiency, environmental and time constraint reasons. Here, we present an innovative method of successive macerations using a mixture of solvents with the aim of simultaneously improving the yield, the partition of the compounds between the different phases and reducing the volume of extraction solvents. Triphasic systems were prepared by mixing five solvents (n-heptane, ethyl acetate, acetonitrile, butan-1-ol, water) in various proportions. To validate this method, the most efficient triphasic system was subsequently used to perform three successive macerations with a polarity gradient on a model plant before being extended to several alpine plants. Our results showed an overall good yield compared to conventional maceration techniques, while improving phase partition and reducing extraction time and volume of solvents.

A Review on Synthesis, Optimization, Mechanism, Characterization, and Antibacterial Application of Silver Nanoparticles Synthesized from Plants

Developments in nanotechnology and natural product research toward the search for novel antibacterial agents have drawn the interest of many scientists to the synthesis of silver nanoparticles (AgNPs) from natural product (especially plants) due to its numerous benefits over other methods of synthesis such as been easy, economical, convenient, and environmental friendly. Aside from the aforementioned advantages, the synthesis of AgNPs from medicinal plant has been reported as the best approach of synthesizing AgNPs with great biological activities due to the numerous biomolecules found in plants. Recently, the number of researches toward the improvement of the yield, morphological properties, analytical techniques, and the development of optimal conditions and exact mechanism for synthesizing AgNPs from plants have been increasing tremendously. In this review, we present a comprehensive report on the recent development in the synthesis, optimization conditions, mechanism, and characterization techniques of AgNPs synthesized from plant extracts. Furthermore, a thorough discussion on the recent advances in the application of AgNPs synthesized from plant as therapeutic agent against bacterial infections was made.

Future Leader to Watch – Fabrizio Alberti

ABSTRACTFuture Leader to Watch is a series of interviews with the first authors of a selection of Reviews published in Biology Open, helping early-career researchers promote themselves alongside their papers. Fabrizio Alberti is first author on ‘Recent developments of tools for genome and metabolome studies in basidiomycete fungi and their application to natural product research’, published in BiO. Fabrizio is a Leverhulme Trust Early Career Fellow (Senior Research Fellow) at the School of Life Sciences and Department of Chemistry, University of Warwick, UK, investigating the discovery and biosynthetic characterisation of natural products made by fungi and bacteria.

Recent developments of tools for genome and metabolome studies in basidiomycete fungi and their application to natural product research.

ABSTRACTBasidiomycota are a large and diverse phylum of fungi. They can make bioactive metabolites that are used or have inspired the synthesis of antibiotics and agrochemicals. Terpenoids are the most abundant class of natural products encountered in this taxon. Other natural product classes have been described, including polyketides, peptides, and indole alkaloids. The discovery and study of natural products made by basidiomycete fungi has so far been hampered by several factors, which include their slow growth and complex genome architecture. Recent developments of tools for genome and metabolome studies are allowing researchers to more easily tackle the secondary metabolome of basidiomycete fungi. Inexpensive long-read whole-genome sequencing enables the assembly of high-quality genomes, improving the scaffold upon which natural product gene clusters can be predicted. CRISPR/Cas9-based engineering of basidiomycete fungi has been described and will have an important role in linking natural products to their genetic determinants. Platforms for the heterologous expression of basidiomycete genes and gene clusters have been developed, enabling natural product biosynthesis studies. Molecular network analyses and publicly available natural product databases facilitate data dereplication and natural product characterisation. These technological advances combined are prompting a revived interest in natural product discovery from basidiomycete fungi.This article has an associated Future Leader to Watch interview with the first author of the paper.

Taking Different Roads: l-Tryptophan as the Origin of Psilocybe Natural Products.

Psychotropic fungi of the genus Psilocybe, colloquially referred to as "magic mushrooms", are best known for their l-tryptophan-derived major natural product, psilocybin. Yet, recent research has revealed a more diverse secondary metabolism that originates from this amino acid. In this minireview, the focus is laid on l-tryptophan and the various Psilocybe natural products and their metabolic routes are highlighted. Psilocybin and its congeners, the heterogeneous blue-colored psilocyl oligomers, alongside β-carbolines and N,N-dimethyl-l-tryptophan, are presented as well as current knowledge on their biosynthesis is provided. The multidisciplinary character of natural product research is demonstrated, and pharmacological, medicinal, ecological, biochemical, and evolutionary aspects are included.

Discovery of Bioactive Compounds from Traditionally used Medicinal Plants: A Profile of Nilufar Z. Mamadalieva

Discovery of Bioactive Compounds from Traditionally used Medicinal Plants: A Profile of Nilufar Z. Mamadalieva

Bioreporters for Direct Mode of Action-Guided Screening of Antibiotic Producer Strains

A big challenge in natural product research of today is rapid dereplication of already known substances, to free capacities for the exploration of new agents. Prompt information on bioactivities and mode of action (MOA) speeds up the lead discovery process of new compounds and may broaden application options when additional targets of known agents are uncovered. Here, we present a bioreporter assay setup as a versatile strategy for combined bioactivity- and MOA-guided primary screening for antibacterial agents. The approach is suitable for directly probing producer strains grown on agar, without need for initial compound enrichment or purification. The application works well along the entire purification pipeline with culture supernatants, extracts, fractions, and pure substances. The biosensors allow for a MOA-guided purification to selectively prioritize metabolic activities of interest. In combination with high-resolution mass spectrometry, the technology is a highly efficient and sensitive tool for rapid compound identification and target deconvolution.