GNPS - Methylobacter Natural Product Discovery
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q-Exactive
ORGANISM(S): Methylobacter Tundripaludum (ncbitaxon:173365)
SUBMITTER: 
Aaron Puri
PROVIDER: MSV000081064 | GNPS | Mon May 08 10:54:00 BST 2017
REPOSITORIES: GNPS
Similar Datasets
Project description:Non-targted LC-MS/MS natural product screening of methane bacterium.
2017-04-20 | MSV000080974 | GNPS
Project description:Non-targted MS/MS Natural Product Screening of three bacterial isolates of the genus Pseudomonas, native from agricultural soils in Argentina, that produce surfactant molecules.
Pseudomonas chlororaphis SMMP3
Pseudomonas sp. SVMP4
Pseudomonas sp. SBMP6
2020-02-26 | MSV000085024 | GNPS
Project description:SARS-CoV-2 virus mimics host mRNA by capping its viral RNA to promote replication and evade host immune sensing. SARS-CoV-2 NSP14 is the N7-guanosine methyltransferase (N7-MTase) responsible for RNA cap-0 formation. Targeting NSP14 for antiviral drug development is an under-explored but promising strategy. Here we conducted a high-throughput screening on natural products library derived from Chinese herbal medicine to discover Emodin as a SARS-CoV-2 NSP14 inhibitor. Exploring Emodin derivatives, Questin was identified with potent cellular inhibitory activity (EC50=249 nM) against SARS-CoV-2, which inhibits NSP14 in an RNA cap competitive manner, making it one the most potent anti-coronaviral natural products. Mechanistically, besides catalyzing viral RNA capping, NSP14 by itself could remodel host transcriptome such as enriching CREBBP, a key host factor in cellular cyclic AMP response pathway, to promote viral infection. As a result, targeting NSP14 by Questin significantly impairs viral Replication & Translation step and reverses host transcriptome remodeled by NSP14. We next validated Questin as a promising lead with significantly improved toxicity upon acute exposure in zebrafish larvae. Taken together, our study not only demonstrates Questin as a potent drug lead for clinical antiviral application, but also highlights multiple antiviral potentials of NSP14 as therapeutic target.
2024-12-31 | GSE282879 | GEO
Project description:Elucidation of genes enhancing natural product biosynthesis through co-evolution analysis
| PRJNA1078415 | ENA
Project description:Streptomyces has the largest repertoire of natural product biosynthetic gene clusters (BGCs), yet developing a universal engineering strategy for each Streptomyces species is challenging. Given that some Streptomyces species have larger BGC repertoires than others, we hypothesized that a set of genes co-evolved with BGCs to support biosynthetic proficiency must exist in those strains, and that their identification may provide universal strategies to improve the productivity of other strains. We show here that genes co-evolved with natural product BGCs in Streptomyces can be identified by phylogenomics analysis. Among the 597 genes that co-evolved with polyketide BGCs, 11 genes in the “coenzyme” category have been examined, including a gene cluster encoding for the co-factor pyrroloquinoline quinone (PQQ). When the pqq gene cluster was engineered into 11 Streptomyces strains, it enhanced production of 16,385 metabolites, including 36 known natural products with up to 40-fold improvement and several activated silent gene clusters. This study provides a new engineering strategy for improving polyketide production and discovering new biosynthetic gene clusters.
2024-03-01 | GSE256209 | GEO
Project description:Natural products represent a rich source for antibiotics addressing versatile cellular targets. The deconvolution of their targets via chemical proteomics is often challenged by the introduction of large photocrosslinkers. Here we select elegaphenone, a largely uncharacterized natural product antibiotic bearing a native benzophenone core scaffold, for affinity-based protein profiling (AfBPP) in Gram-positive and Gram-negative bacteria. This study utilizes the alkynylated natural product scaffold as a probe to uncover intriguing biological interactions with the transcriptional regulator AlgP. Furthermore, proteome profiling of a Pseudomonas aeruginosa AlgP transposon mutant revealed unique insights into the mode of action. Elegaphenone enhanced the killing of intracellular P. aeruginosa in macrophages exposed to sub-inhibitory concentrations of the fluoroquinolone antibiotic norfloxacin.
2021-09-08 | PXD010476 | Pride
Project description:Fungal secondary metabolites represent a rich and largely untapped source for bioactive molecules, including peptides with substantial structural diversity and pharmacological potential. As methods proceed to take a deep dive into fungal genomes, complimentary methods to identify bioactive components are required to keep pace with the expanding fungal repertoire. We developed PepSAVI-MS to expedite the search for natural product bioactive peptides and herein demonstrate proof-of-principle applicability of the pipeline for the discovery of bioactive peptides from fungal secretomes via identification of the antifungal killer toxin KP4 from Ustilago maydis P4. This work opens the door to investigating microbial secretomes with a new lens, and could have broad applications across human health, agriculture, and food safety.
2018-02-19 | PXD006931 | Pride
Project description:Fungi are known for their diverse biologically active secondary metabolites, compounds that have provided the basis for many landmark therapeutics in the last century. Due to ease of collection and culturing, the existing fungal chemical literature is vast, and fungal natural product isolation can often be hindered by the numerous nuisance and pan-toxic compounds that many strains produce. Dereplication efforts, aimed at identifying such compounds early in the purification, are imperative to reduce time and expense of rediscovery of known metabolites. The common practice of dereplication then deprioritizes samples containing nuisance compounds and often excludes them from the drug discovery workflow. We have implemented a two-step dereplication protocol that uses tandem mass spectrometry to identify nuisance compounds, followed by mass-directed chromatographic editing to remove them while leaving the remaining 'edited extract' in the drug discovery workflow. This two-step strategy facilitates rapid and more accurate evaluation of the chemical potential of high-throughput extract screening campaigns by consideration of bioactivity beyond that triggered by known metabolites. We demonstrate the isolation of a new natural product antibiotic from an otherwise toxic extract using the technique.
| S-EPMC6800021 | biostudies-literature
Project description:Leishmaniasis is a Neglected Tropical Disease caused by the insect-vector borne protozoan parasite, Leishmania species. Infection affects millions of the World’s poorest, however vaccines are absent and drug therapy limited. Recently, public-private partnerships have developed to identify new modes of controlling leishmaniasis. Most of these collaborative efforts have relied upon the small molecule synthetic compound libraries held by industry, but the number of New Chemical Entities (NCE) identified and entering development as antileishmanials has been very low. In light of this, here we describe a public-private effort to identify natural products with activity against Leishmania mexicana, a causative agent of cutaneous leishmanaisis (CL). Utilising Hypha Discovery’s fungal extract library which is rich in small molecule (<500 molecular weight) secondary metabolites, we undertook an iterative phenotypic screening and fractionation approach to identify potent and selective antileishmanial hits. This led to the identification of a novel oxidised bisabolane sequiterpene which demonstrated activity in an infected cell model and was shown to disrupt multiple processes using a metabolomic approach. In addition, and importantly, this study also sets a precedent for new approaches for CL drug discovery.
2021-02-12 | MTBLS868 | MetaboLights
Project description:This review seeks to provide a timely survey of the scope and limitations of cheminformatics methods in natural product-based drug discovery. Following an overview of data resources of chemical, biological and structural information on natural products, we discuss, among other aspects, in silico methods for (i) data curation and natural products dereplication, (ii) analysis, visualization, navigation and comparison of the chemical space, (iii) quantification of natural product-likeness, (iv) prediction of the bioactivities (virtual screening, target prediction), ADME and safety profiles (toxicity) of natural products, (v) natural products-inspired de novo design and (vi) prediction of natural products prone to cause interference with biological assays. Among the many methods discussed are rule-based, similarity-based, shape-based, pharmacophore-based and network-based approaches, docking and machine learning methods.
| S-EPMC7757247 | biostudies-literature