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Data Fusion-based Discovery (DAFdiscovery) is a pipeline designed to help users combine mass spectrometry (MS), nuclear magnetic resonance (NMR), and bioactivity data in a notebook-based application to accelerate annotation and discovery of bioactive compounds. It applies Statistical Total Correlation Spectroscopy (STOCSY) and Statistical HeteroSpectroscopy (SHY) calculation in their data using an easy-to-follow Jupyter Notebook.Different case studies are presented for benchmarking, and the resultant outputs are shown to aid natural products identification and discovery. The goal is to encourage users to acquire MS and NMR data from their samples (in replicated samples and fractions when available) and to explore their variance to highlight MS features, NMR peaks, and bioactivity that might be correlated to accelerated bioactive compound discovery or for annotation-identification studies.Different applications were demonstrated using data from different research groups, and it was shown that DAFdiscovery reproduced their findings using a more straightforward method.DAFdiscovery has proven to be a simple-to-use method for different situations where data from different sources are required to be analyzed together.

DAFdiscovery is a pipeline designed to help users combine NMR, MS and bioactivity data in a notebook-based application to accelerate annotation and discovery of bioactive compounds. It applies Statistical Total Correlation (STOCSY) and Statistical HeteroSpectroscopy (SHY) calculation in their data using an easy-to-follow Jupyter Notebook. Different case studies are presented for benchmarking, and the resultant outputs are shown to aid natural products identification and discovery. The goal is to encourage users to acquire MS and NMR data from their samples (in replicated samples and fractions when available) and to explore their variance to highlight MS features, NMR peaks, and bioactivity that might be correlated to accelerate bioactive compound discovery or for annotation-identification studies.

Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. Nonetheless, the absence of biotic and abiotic interactions generally observed in nature still limit the chemical diversity and leads to "poorer" chemical profiles. Nowadays, several methods have been developed to determine the conditions under which cryptic genes are activated, in an attempt to induce these silenced biosynthetic pathways. Among those, the one strain, many compounds (OSMAC) strategy has been applied to enhance metabolic production by a systematic variation of growth parameters. The complexity of the chemical profiles from OSMAC experiments has required increasingly robust and accurate techniques. In this sense, deconvolution-based 1 HNMR quantification have emerged as a promising methodology to decrease complexity and provide a comprehensive perspective for metabolomics studies. Our present work shows an integrated strategy for the increased production and rapid quantification of compounds from microbial sources. Specifically, an OSMAC design of experiments (DoE) was used to optimize the microbial production of bioactive fusaric acid, cytochalasin D and 3-nitropropionic acid, and Global Spectral Deconvolution (GSD)-based 1 HNMR quantification was carried out for their measurement. The results showed that OSMAC increased the production of the metabolites by up to 33% and that GSD was able to extract accurate NMR integrals even in heavily coalescence spectral regions. Moreover, GSD-1 HNMR quantification was reproducible for all species and exhibited validated results that were more selective and accurate than comparative methods. Overall, this strategy up-regulated important metabolites using a reduced number of experiments and provided fast analyte monitor directly in raw extracts.

MOLECULAR NETWORKS: AN ANALYSIS ON ANNOTATIONS AND DISCOVERY OF NEW ASSETS. To speed up the discovery of bioactive natural products (NP), chemists have sought advanced approaches in analytical and computational chemistry in attempt to organize and extract information from large data sets. In this sense, the molecular networks (MN) successfully organized enormous sets of mass spectrometry (MS) data together with samples metadata information in an intuitive visualization in the spectral similarity networks format. GNPS (Global Natural Products Social Molecular Networking), a free online platform for storing and processing MSn data, is a leading application of spectral matching with public databases aimed at the dereplication and discovery of new bioactive products through molecular networks. In this review, we address the concept of GNPS spectral similarity networks, as well as their complementary computational tools, benefits and limitations applied in NP studies associated with dereplication, chemical ecology, functional genetics and determination of biosynthetic pathways.

Graphical abstract, Introduction Natural products of pharmaceutical interest often do not reach the drug market due to the associated low yields and difficult extraction. Knowledge of biosynthetic pathways is a key element in the development of biotechnological strategies for plant specialized metabolite production. Erythrina species are mainly used as central nervous system depressants in folk medicine and are important sources of bioactive tetracyclic benzylisoquinoline alkaloids (BIAs), which can act on several pathology-related biological targets. Objectives In this sense, in an unprecedented approach used with a non-model Fabaceae species grown in its unique arid natural habitat, a combined transcriptome and metabolome analyses (seeds and leaves) is presented. Methods The Next Generation Sequencing-based transcriptome (de novo RNA sequencing) was carried out in a NextSeq 500 platform. Regarding metabolite profiling, the High-resolution Liquid Chromatography was coupled to DAD and a micrOTOF-QII mass spectrometer by using electrospray ionization (ESI) and Time of Flight (TOF) analyzer. The tandem MS/MS data were processed and analyzed through Molecular Networking approach. Results This detailed macro and micromolecular approach applied to seeds and leaves of E. velutina revealed 42 alkaloids, several of them unique. Based on the combined evidence, 24 gene candidates were put together in a putative pathway leading to the singular alkaloid diversity of this species. Conclusion Overall, these results could contribute by indicating potential biotechnological targets for modulation of erythrina alkaloids biosynthesis as well as improve molecular databases with omic data from a non-model medicinal plant, and reveal an interesting chemical diversity of Erythrina BIA harvested in Caatinga.

Made available in DSpace on 2020-12-11T17:20:23Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-05-20 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Rationale Clerodane-type diterpenes from Casearia species show important pharmacological activites such as antitumor, antimicrobial and anti-inflamatory. There are several mass spectrometry (MS)-based methods for identification of diterpenes; however, there is still a lack of MS procedures capable of providing characteristic fragmentation pathways for a rapid and unambiguous elucidation of casearin-like compounds. Methods Casearin-like compounds were investigated by electrospray ionization tandem mass spectrometry (ESI-MS/MS). The fragmentation studies were carried out by tandem mass spectrometry in space (quadrupole time-of-flight (QTOF)) using different collision energies and also by tandem mass spectrometry in time (QIT) by selective isolation of product ions. Results Casearin-like compounds presented a predominance of sodium- and potassium-cationized precursor ions. Both QIT and QTOF techniques provided sequential neutral losses of esters related to the R-1 to R-5 substituents linked to the nucleus of the clerodane diterpenes. The fragmentation pathway is initiated with a cleavage of the ester moieties R-2 followed by the elimination of the ester groups R-3, both losing neutral carboxylic acids. Using QIT, it was also possible to observe the cleavage of the ester groups R-1 or R-5 by MS4 experiments. Conclusions Through a rational analysis of the fragmentation mechanisms of Casearia diterpenes it was possible to suggest an annotation strategy based on the sequential cleavages of the ester groups related to the R-2, R-3 and R-5 substituents. These results will assist studies of the dereplication and metabolomics involving casearin-like compounds present in complex extracts of Casearia species. Univ Sao Paulo, Ribeirao Preto Sch Pharmaceut Sci, Ribeirao Preto, SP, Brazil Univ Fed Uberlandia, Inst Chem, Uberlandia, MG, Brazil Sao Paulo State Univ, Sch Pharmaceut Sci, Lab Pharmacognosy, Araraquara, SP, Brazil York Univ, Dept Chem, Ctr Res Mass Spectrometry, Toronto, ON, Canada Sao Paulo State Univ, Inst Chem, Araraquara, SP, Brazil Imperial Coll London, Dept Life Sci, Silwood Pk Campus, Ascot, Berks, England Univ Fed Piaui, Chem Dept, Teresina, Piaui, Brazil Sao Paulo State Univ, Sch Pharmaceut Sci, Lab Pharmacognosy, Araraquara, SP, Brazil Sao Paulo State Univ, Inst Chem, Araraquara, SP, Brazil CNPq: 207745/2014-5 CNPq: INCT 465637/2014-0 CAPES: 001 FAPESP: 2011/21440-3 FAPESP: 2012/23775-5 FAPESP: 2013/07600-3 FAPESP: 2014/50926-0 FAPESP: 2016/13292-8 FAPESP: 2017/19702-6

Made available in DSpace on 2020-12-12T01:10:10Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-04-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Soybeans are among the world's major crops responsible for food and biodiesel production, as well as a major source of isoflavones – a class of high value-added bioactive compounds. As estimated 460 million tonnes of soya residues (branches, leaves, roots, and pods) will be produced in the 2018/2019 harvest, and 20–40% of this waste must be removed from the field to ensure soil quality and minimize environmental impacts. This work investigated the potential occurrence and content of isoflavones in soya agricultural waste collected directly from the ground after mechanically harvesting. We also assessed the extraction performances of ethanol and acetone for these materials as an alternative to acetonitrile, a problematic solvent from an environmental point of view. Considerable amounts of isoflavones were found in soya agricultural waste collected directly from the ground when compared to soybeans (2.71 ± 0.27, 0.57 ± 0.1, 0.30 ± 0.05 and 2.09 ± 0.24 kg of isoflavones/tonne of leaves, branches, pods, and soybeans, respectively). The greener ethanol and acetone performed well for a broad range of compounds. This is an example in which appreciable amounts of high value-added compounds are wasted. Since isoflavones are considered phytoestrogens, their recovery from part of this waste might avoid potential contamination of soil and groundwater. UNESP – São Paulo State University Faculty of Agricultural Sciences USP – University of São Paulo Faculty of Pharmaceutical Sciences of Ribeirão Preto UNESP – São Paulo State University School of Sciences UNESP – São Paulo State University Institute of Chemistry UNESP – São Paulo State University Faculty of Agricultural Sciences UNESP – São Paulo State University School of Sciences UNESP – São Paulo State University Institute of Chemistry FAPESP: 2014/50926-0 FAPESP: 2016/08179-8 FAPESP: 2016/13292-8 FAPESP: 2017/06216-6 CNPq: 453928/2014-5

Made available in DSpace on 2022-04-28T19:40:14Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-05-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) CYTED Ciencia y Tecnología para el Desarrollo Natural Environment Research Council Newton Fund Understanding of tropical forests has been revolutionized by monitoring in permanent plots. Data from global plot networks have transformed our knowledge of forests’ diversity, function, contribution to global biogeochemical cycles, and sensitivity to climate change. Monitoring has thus far been concentrated in rain forests. Despite increasing appreciation of their threatened status, biodiversity, and importance to the global carbon cycle, monitoring in tropical dry forests is still in its infancy. We provide a protocol for permanent monitoring plots in tropical dry forests. Expanding monitoring into dry biomes is critical for overcoming the linked challenges of climate change, land use change, and the biodiversity crisis. Tropical Biodiversity Royal Botanic Garden Edinburgh School of Geography Faculty of Environment University of Leeds Fundación Ecosistemas Secos de Colombia School of Geosciences The University of Edinburgh Geography College of Life and Environmental Sciences University of Exeter Instituto de Pesquisas Jardim Botanico do Rio de Janeiro Centro de Ecologia Instituto Venezolano de Investigaciones Cientificas Ciencias Básicas de la Biodiversidad Instituto de Investigación de Recursos Biológicos Alexander von Humboldt Herbario Departamento Académico de Biología Universidad Nacional Agraria La Molina Center for Conservation and Sustainability Smithsonian Conservation Biology Institute Department of Life Sciences Imperial College London Laboratório de Ciências Ambientais Universidade Estadual do Norte Fluminense Instituto de Investigaciones en Ciencias Agrarias de Rosario (IICAR) Facultad Ciencias Agrarias UNR Universidad Nacional de Rosario Escuela de Biología Facultad de Ciencias Exactas Pontificia Universidad Católica del Ecuador Real Jardín Botánico CSIC Laboratório de Ciências Ambientas Universidade Estadual do Norte Fluminense Departamento de Biologia Faculdade de Filosofia Ciências e Letras de Ribeirão Preto Universidade de Sao Paulo Museo de Historia Natural Noel Kempff Mercado Universidad Autonoma Gabriel Rene Moreno Unidade Acadêmica de Garanhuns Universidade Federal Rural de Pernambuco Instituto de Biologia Universidade Federal da Bahia International Master Program of Agriculture National Chung Hsing University Departamento de Biologia Vegetal Universidade Federal do Ceará Centro de Tecnologia e Recursos Naturais (CTRN) Universidade Federal de Campina Grande Programa de Pós-Graduação em Ciências Biológicas (PPGCB) Centro Ciências Biológicas e da Saúde Universidade Estadual de Montes Claros Ciencias Biologicas Universidade Estadual de Feira de Santana Grupo de Ecología y Conservación de Fauna y Flora Silvestre Universidad Nacional de Colombia Facultad de Ciencias Instituto de Investigaciones sobre los Recursos Naturales Universidad Michoacana de San Nicolás de Hidalgo Universidade do Estado de Mato Grosso Herbario HOXA Jardín Botánico de Missouri Embrapa Semiárido Embrapa Biologia Vegetal Universidade Federal de Minas Gerais Faculdade de Ciências Farmacêuticas de Ribeirão Preto Universidade de Sao Paulo Laboratório de Fenologia Departamento de Botânica Instituto de Biociências Universidade Estadual Paulista Departamento de Biologia Vegetal Universidade Federal de Viçosa Departamento de Ciências Florestais Universidade Federal de Lavras Department of Forest Sciences Universidade Federal Rural de Pernambuco Departamento de Ciências Atmosféricas Instituto de Astronomia Geofífisica e Ciências Atmosféricas Universidade de São Paulo Plant Ecology and Nature Conservation Wageningen University and Research Laboratório de Fenologia Departamento de Botânica Instituto de Biociências Universidade Estadual Paulista FAPESP: 2015/50488-5 CYTED Ciencia y Tecnología para el Desarrollo: 418RT0554 Natural Environment Research Council: NE/I027797/1 Natural Environment Research Council: NE/I028122/1 Newton Fund: NE/N000587/1 Newton Fund: NE/N01247X/1 Newton Fund: NE/N012550/1

Metabolomics has played a central role in various areas of plant sciences, offering new perspectives for the advancement of agriculture, drug discovery, chemical ecology and taxonomy. Plant metabolomics (identification and quantification) aims to understand the relationship between biological systems and genetic, pathological and or environmental stimuli in terms of differential expression of the metabolism. Owing to the unique challenges, such studies require multidisciplinary skills involving biology, chemistry, statistics, and computer science for the extraction and complete understanding of information. In this sense, this review summarizes the main procedures that involve the steps of plant metabolomic study (design of experiments, sample preparation, analytical methods and data analysis), providing a comprehensive overview, showing the main challenges and limitations and possible solutions for the different approaches used.

Chlorogenic acids (CGAs) are known as an important class of natural products found in different plant species and are of great interest in diverse research fields. Described as powerful antioxidant...

Piperlongumine is an amide alkaloid found in Piperaceae species that shows a broad spectrum of biological properties, including antitumor and antiparasitic activities. Herein, the leishmanicidal effect of piperlongumine and its derivatives produced by a biomimetic model using metalloporphyrins was investigated. The results showed that IC50 values of piperlongumine in promastigote forms of Leishmania infantum and Leishmania amazonensis were 7.9 and 3.3 µM, respectively. The IC50 value of piperlongumine in the intracellular amastigote form of L. amazonensis was 0.4 µM, with a selectivity index of 25. The piperlongumine biomimetic derivatives, Ma and Mb, also showed leishmanicidal effects. We also carried out an in vitro metabolic degradation study showing that Ma is the most stable piperlongumine derivative in rat liver microsome incubations. The results presented here indicate that piperlongumine is a potential leishmanicidal candidate and support the biomimetic approach for development of new antileishmanial derivatives.

Made available in DSpace on 2020-12-12T01:51:57Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-11-01 Technological advances have contributed to the evolution of the natural product chemistry and drug discovery programs. Recently, computational methods for nuclear magnetic resonance (NMR) and mass spectrometry (MS) have speeded up and facilitated the process of structural elucidation even in high complex biological samples. In this chapter, the current computational tools related to NMR and MS databases and spectral similarity networks, as well as their applications on dereplication and determination of biological biomarkers, are addressed. Nuclei of Bioassays Biosynthesis and Ecophysiology of Natural Products (NuBBE) Department of Organic Chemistry Institute of Chemistry São Paulo State University (UNESP), Av. Prof. Francisco Degni, 55 Nucleus of Research in Natural Products and Synthetics Dep. Physics and Chemistry Faculty of Pharmaceutical Sciences of Ribeirão Preto São Paulo University Dept. Biology/CEIS Institute of Biosciences of Rio Claro São Paulo State University (UNESP), Av. 24A n.1515 Medway Metabonomics Research Group University of Greenwich (UoG) Nuclei of Bioassays Biosynthesis and Ecophysiology of Natural Products (NuBBE) Department of Organic Chemistry Institute of Chemistry São Paulo State University (UNESP), Av. Prof. Francisco Degni, 55 Dept. Biology/CEIS Institute of Biosciences of Rio Claro São Paulo State University (UNESP), Av. 24A n.1515

The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic exploration and natural products discovery. To achieve this goal, plant metabolomics relies on accurate and selective acquisition of all possible chemical information, which includes maximization of the number of detected metabolites and their correct molecular assignment. Nuclear magnetic resonance (NMR) spectroscopy has been recognized as a powerful platform for obtaining the metabolite profiles of plant extracts. In this chapter, we provide a workflow for targeted and untargeted metabolite profiling of plant extracts using both 1D and 2D NMR methods. The protocol includes sample preparation, instrument operation, data processing, multivariate analysis, biomarker elucidation, and metabolite quantitation. It also addresses the annotation of plant metabolite peaks considering NMR's capabilities to cover a broad range of metabolites and elucidate structures for unknown compounds.

Structure elucidation is an important and sometimes time-consuming step for natural products research. This step has evolved in the past few years to a faster and more automated process due to the development of several computational programs and analytical techniques. In this paper, the topics of NMR prediction and CASE programs are addressed. Furthermore, the elucidation of natural peptides is discussed.

The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic exploration and natural products discovery. To achieve this goal, plant metabolomics relies on accurate and selective acquisition of all possible chemical information, which includes maximization of the number of detected metabolites and their correct molecular assignment. Nuclear magnetic resonance (NMR) spectroscopy has been recognized as a powerful platform for obtaining the metabolite profiles of plant extracts. In this chapter, we provide a workflow for targeted and untargeted metabolite profiling of plant extracts using both 1D and 2D NMR methods. The protocol includes sample preparation, instrument operation, data processing, multivariate analysis, biomarker elucidation, and metabolite quantitation. It also addresses the annotation of plant metabolite peaks considering NMR's capabilities to cover a broad range of metabolites and elucidate structures for unknown compounds.

Flavonoids represent an important class of natural products with a central role in plant physiology and human health. Their accurate annotation using untargeted mass spectrometry analysis still relies on differentiating similar chemical scaffolds through spectral matching to reference library spectra. In this work, we combined molecular network analysis with rules for fragment reactions and chemotaxonomy to enhance the annotation of similar flavonoid glyconjugates. Molecular network topology progressively propagated the flavonoid chemical functionalization according to collision-induced dissociation (CID) reactions, as the following chemical attributes: aglycone nature, saccharide type and number, and presence of methoxy substituents. This structure-based distribution across the spectral networks revealed the chemical composition of flavonoids across intra- and interspecies and guided the putatively assignment of 64 isomers and isobars in the Chrysobalanaceae plant species, most of which are not accurately annotated by automated untargeted MS2 matching. These proof of concept results demonstrate how molecular networking progressively grouped structurally related molecules according to their product ion scans, abundances, and ratios. The approach can be extrapolated to other classes of metabolites sharing similar structures and diagnostic fragments from tandem mass spectrometry.

A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 μL sample volume, 3.0 mL min(-1) flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i-propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 μL sample volume, 2.0 mL min(-1) flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols.

China is an important center of origin for the genus Citrus L. of the family Rutaceae and is rich in wild Citrus species. The taxonomy of Citrus has been a subject of controversy for more than a half century. We propose that the metabolite profiles of Chinese native Citrus species can be used for classification and understanding of the taxonomic relationships within the Citrus germplasm. In this study, triplicate gas chromatography–mass spectrometry (GC–MS) metabolite profiles of 20 Citrus species/varieties were acquired, including 10 native varieties originating in China. R-(+)-limonene, α-pinene, sabinene and α-terpinene were found to be major characteristic components of the essential oils analyzed in this study, and these compounds contributed greatly to the metabolic classification. The three basic species of the subgenus Eucitrus (Swingle’s system), i.e., C. reticulata Blanco, C. medica L. and C. grandis Osb., were clearly differentiated based upon their metabolite profiles using hierarchical cluster analysis (HCA) and partial least square-discriminant analysis (PLS-DA). All the presumed hybrid genotypes, including sweet orange (C. sinensis Osb.), sour orange (C. aurantium L.), lemon (C. limon Burm.f.), rough lemon (C. jambhiri Lush.), rangpur lime (C. limonia Osb.) and grapefruit (C. paradisi Macf.), were grouped closely together with one of their suggested parent species in the HCA-dendrogram and the PLS-DA score plot. These results clearly demonstrated that the metabolite profiles of Citrus species could be utilized for the taxonomic classification of the genus and are complementary to the existing taxonomic evidence, especially for the identification and differentiation of hybrid species.

Over the last few decades, an unprecedented amount of data has emerged as a result of a new way of obtaining knowledge: an exploratory and integrative analysis of data sets called a holistic approach. In the life sciences, this holistic view is represented by the systems biology approach that aims to understand the functioning of organisms and their interactions with the environment through the study of the integration of stratified levels of molecular information that begin in gene expression and culminate in phenotypic characteristics. To deal with this plurality of information, ″knowledge discovery in databases″ has been implemented in several areas of chemical biology and has promoted the collection, storage and processing of multivariate data. Throughout this chapter we intend to explore the main databases of chemical biology used, highlighting the areas of proteomics, metabolomics, natural products and medicinal chemistry, as well as providing a brief discussion on the current status of the integration of ″omics″ knowledge available in databases.

Made available in DSpace on 2018-12-11T17:13:50Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-12-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The intrinsic value of biodiversity extends beyond species diversity, genetic heritage, ecosystem variability and ecological services, such as climate regulation, water quality, nutrient cycling and the provision of reproductive habitats it is also an inexhaustible source of molecules and products beneficial to human well-being. To uncover the chemistry of Brazilian natural products, the Nuclei of Bioassays, Ecophysiology and Biosynthesis of Natural Products Database (NuBBEDB) was created as the first natural product library from Brazilian biodiversity. Since its launch in 2013, the NuBBEDB has proven to be an important resource for new drug design and dereplication studies. Consequently, continuous efforts have been made to expand its contents and include a greater diversity of natural sources to establish it as a comprehensive compendium of available biogeochemical information about Brazilian biodiversity. The content in the NuBBEDB is freely accessible online (https://nubbe.iq.unesp.br/portal/nubbedb.html) and provides validated multidisciplinary information, chemical descriptors, species sources, geographic locations, spectroscopic data (NMR) and pharmacological properties. Herein, we report the latest advancements concerning the interface, content and functionality of the NuBBEDB. We also present a preliminary study on the current profile of the compounds present in Brazilian territory. Nuclei of Bioassays Biosynthesis and Ecophysiology of Natural Products (NuBBE) Department of Organic Chemistry Institute of Chemistry Sao Paulo State University - UNESP Centro de Imagens e Espectroscopia in Vivo Por Ressonância Magnética Institute of Physics of Sao Carlos University of Sao Paulo - USP Laboratório de Química Medicinal e Computacional (LQMC) Centro de Pesquisa e Inovação em Biodiversidade EFármacos Institute of Physics of Sao Carlos University of Sao Paulo - USP Nuclei of Bioassays Biosynthesis and Ecophysiology of Natural Products (NuBBE) Department of Organic Chemistry Institute of Chemistry Sao Paulo State University - UNESP

Artepillin C, a natural product present in the Brazilian green propolis, has several biological properties. Among these properties, the antitumor action of this product is noteworthy and makes it a promising drug candidate for the treatment of several types of cancer. This paper describes the in vitro metabolism of Artepillin C in rat and human liver microsomes. The rat model suggested a sigmoidal profile for the metabolism, adapted to the Hillʼs kinetic model. The enzymatic kinetic parameters were as follows: maximal velocity = 0.757 ± 0.021 µmol/mg protein/min, Hill coefficient = 10.90 ± 2.80, and substrate concentration at which half-maximal velocity of a Hill enzyme is achieved = 33.35 ± 0.55 µM. Based on these results, the calculated in vitro intrinsic clearance for Artepillin C was 16.63 ± 1.52 µL/min/mg protein. The in vitro metabolism assay conducted on the human model did not fit any enzymatic kinetic model. Two novel metabolites were formed in both mammal microsomal models and their chemical structures were elucidated for the first time. The main human cytochrome P450 isoforms involved in Artepillin C metabolism had been identified, and the results suggest a majority contribution of CYP2E1 and CYP2C9 in the formation of the two metabolites.

Made available in DSpace on 2018-11-26T17:06:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-09-29 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) INCT-if Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) University of Sao Paulo Piperlongumine (PPL), a natural plant product, has been extensively studied in cancer treatment going up on clinical trials. Since the first report related to its use on cancer research (in 2011) around 80 papers have been published in less than 10 years, but a gap still remaining. There are no metabolism studies of PPL in human organism. For the lack of a better view, here, the CYP450 in vitro oxidation of PPL was described for the first time. In addition, the enzymatic kinetic data, the predicted in vivo parameters, the produced metabolites, the phenotyping study and possible piperlongumine-drug interactions in vivo is presented. Univ Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, Dept Ciencias Farmaceut, BR-14040903 Ribeirao Preto, SP, Brazil Univ Sao Paulo, Dept Quim, Fac Filosofia Ciencias & Letras Ribeirao Preto, BR-14040901 Ribeirao Preto, SP, Brazil Univ Fed Rio de Janeiro, Lab Prod Bioat, Campus Macae IMMT, BR-27930560 Macae, RJ, Brazil Sao Paulo State Univ UNESP, Inst Chem, Dept Organ Chem, Nucleus Bioassays Biosynthesis & Ecophysiol Nat P, Araraquara, SP, Brazil Univ Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, Nucleo Pesquisa Prod Nat & Sintet NPPNS, BR-14040903 Ribeirao Preto, SP, Brazil Sao Paulo State Univ UNESP, Inst Chem, Dept Organ Chem, Nucleus Bioassays Biosynthesis & Ecophysiol Nat P, Araraquara, SP, Brazil FAPESP: 2012/0188-4 FAPESP: 2013/17658-9 FAPESP: 2014/23604-1 FAPESP: 2014/50265-3 CNPq: 010143/2011-4 CNPq: 442384/2014-9 CNPq: 306385/2011-2 University of Sao Paulo: 2012.1.17587.1.1

A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 μL sample volume, 3.0 mL min(-1) flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i-propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 μL sample volume, 2.0 mL min(-1) flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols.

Sao Paulo State Univ, Nucleus Bioassays Biosynth & Ecophysiol Nat Prod, Dept Organ Chem, NuBBE,Inst Chem, BR-14800900 Sao Paulo, Brazil

A rational and selective method using on-line high-performance liquid chromatography (HPLC) coupled with electrospray quadrupole time-of-flight tandem mass spectrometry (ESI-QToF-MS/MS) was established for the dereplication of phenolic derivatives from Qualea grandiflora and Qualea cordata. The selection of the extracts was based on the antioxidant capacity measured by in vitro DPPH assay. The HPLC-ESI-QToF-MS/MS analysis was conducted by on-flow detection, using high-resolution mass/ratio ions as well as collision induced MS/MS experiments for selected protonated ions. The dereplication of the EtOAc fraction from the hydro-alcohol extract from the stem bark of Q. grandiflora allowed the detection of the flavonoids: 3',4',5',5,6,7-hexahydroxy-8-methylflavanone, 8-methyl-naringenine and 3',7-dimethoxy-8-methyl-4',5,7-trihydroxyflavanone, as well as a benzophenone derivatives: bis(4,6-dimethoxy-2-hydroxy-3-methylphenyl)-metanone, 3',4'-dimethoxy-8-methyl-5,6,7-trihydroxyflavanone, 7-methoxy-6-methyl-3',4',5-trihydroxyflavanone, 6,8-dimethyl-3'-methoxy-4',5,7-trihydroxyflavanone and 3',5'-dimethoxy-6,8-dimethyl-4',5,7-trihydroxyflavanone were detected in the EtOAc fraction from the hydro-alcohol extract from the leaves of Q. cordata. Um método racional e seletivo de cromatografia de alta eficiência acoplado à espectrometria de massas (CLAE-EM) com ionização por electrospray e analisador do tipo quadrupolo em tempo-de-voo em sequência (ESI-QToF-MS/MS) foi desenvolvido para a desreplicação de derivados fenólicos presentes em Qualea grandiflora e Qualea cordata. Os extratos para a análise foram selecionados por meio dos resultados de atividade antioxidante revelados no ensaio in vitro com DPPH. A análise por HPLC-ESI-QToF-MS/MS foi realizada por detecção contínua das relações massa/carga em alta resolução e pela técnica MS/MS de colisão induzida para fragmentação dos íons moleculares selecionados. A desreplicação da fração AcOEt do extrato hidroalcoólico dos caules de Q. grandiflora permitiu a detecção dos flavonoides: 3',4',5',5,6,7-hexahidroxi-8-metilflavanona, 8-metil-naringenina e 3',7-dimetoxi-8-metil-4',5,7-trihidroxiflavanona, assim como os derivativos da benzofenona (bis(4,6-dimetoxi-2-hidroxi-3-metilfenil)-metanona, 3',4'-dimetoxi-8-metil-5,6,7-trihidroxiflavanona, 7-metoxi-6-metil-3',4',5-trihidroxiflavanona, 6,8-dimetil-3'-metoxi-4',5,7-trihidroxiflavanona e 3',5'-dimetoxi-6,8-dimetil-4',5,7-trihidroxiflavanona) foram detectados na fração AcOEt do extrato hidroalcoólico das folhas de Q. cordata.

Jatropha gossypifolia has been used quite extensively by traditional medicine for the treatment of several diseases in South America and Africa. This medicinal plant has therapeutic potential as a phytomedicine and therefore the establishment of innovative analytical methods to characterise their active components is crucial to the future development of a quality product.To enhance the chromatographic resolution of HPLC-UV-diode-array detector (DAD) experiments applying chemometric tools.Crude leave extracts from J. gossypifolia were analysed by HPLC-DAD. A chromatographic band deconvolution method was designed and applied using interval multivariate curve resolution by alternating least squares (MCR-ALS).The MCR-ALS method allowed the deconvolution from up to 117% more bands, compared with the original HPLC-DAD experiments, even in regions where the UV spectra showed high similarity. The method assisted in the dereplication of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside.The MCR-ALS method is shown to be a powerful tool to solve problems of chromatographic band overlapping from complex mixtures such as natural crude samples.