List of Natural Products databases mentioned in scientific litterature since 2000The Table1_s3 is the most recent version.The table "stereoOverlapTable" references the percentage of agreement in terms of stereochemistry between databases when the latter share molecules.

A structure database of natural products in SDF format was created from the LOTUS database version 9 .

This database is intended to facilitate the dereplication of natural products.

The LOTUS database was described in this publication (free download).

File 220916_frozen_metadata.csv was downloaded from the LOTUS database version 9 and the SMILES chains of the compounds were collected.

The SMILES chains were translated to 2D chemical structures using python scripts relying on the RDKit library.

Each compound was associated to predicted 13C NMR chemical shifts by means of an already reported procedure (free download).

Each compound was also supplemented with metadata from file 220916_frozen_metadata.csv .

Archive file acd_lotusv9.sdf.zip contains acd_lotusv9.sdf with 218,478 compound descriptions inside.

Archive file acd_lotusv9.NMRUDB.zip is a compressed version of acd_lotusv9.NMRUDB, itself created by importation of file acd_lotusv9.sdf in an ACD/Labs database file (new with version 0.0.4).

The description of the first compound was copied in file firstmolv9.sdf and is provided for a quick inspection of the database content.

The title line in firstmolv9.sdf is Q43656_2, meaning that more data about this compound may be found by searching in Wikidata for Q43656 and that the initial data was given by line 2 in file 220916_frozen_metadata.csv .

Files acd_lotusv9.sdf acd_lotusv9.NMRUDB contain biological taxonomy data from file 220916_frozen_metadata.csv that were not exploited in acd_lotusv7. Sub-files dealing with a particular taxon can be easily produced now.

Chemical shift calculations for 13C nuclei using the HOSE code approach are available here for the compounds in acd_lotusv7.

A continuation of the "Phytochemistry of Australian Plants" database compiled by David Collins and Don McGilvery. Contains chemical structures, references, species names, with persistent identifiers to the literature and Atlas of Living Australia (ALA) for geographical distributions. The current curation effort here adds DOIs/ISBNs/ISSNs for ~80% of references, persistent IDs for all species or genus to the ALA or other datasets, and validated structures (smiles) for ~70% of structures. No new entries have been added since the last update to the original database in 2022. Change log is in the README file.

Data provided here was obtained by the listed authors on linked publications, and these authors may have no association with CSIRO. CSIRO acknowledges that the publications linked here may contain Indigenous Cultural and Intellectual Property (ICIP), including traditional knowledge. CSIRO recognizes that First Nations peoples have the right to control, own and maintain their ICIP in accordance with Article 31 of the United Nations Declaration on the Rights of Indigenous Peoples. Users of this dataset may need to obtain permission from First Nations peoples for use of the information in linked publications. Users intending to collect and use biological specimens containing the compounds described in the dataset may also require permission of First Nations peoples, and may require permits and access permission from landholders. Recognizing that any ICIP in the linked publications is already publicly available but that the publications are not readily accessible by First Nations peoples, CSIRO is committed to finding ways to make the ICIP in these publications more findable and accessible to the First Nations communities from which the knowledge was originally obtained. Users should be aware that because of the historical context of some of the linked publications, they may contain words, descriptions, images or terms which may be culturally sensitive and/or offensive and that reflect authors’ views, or those of the period in which the content was created but may not be considered appropriate today. If First Nations people identify content within this dataset that they consider breaches cultural protocols they are encouraged to contact CSIRO on csiroenquiries@csiro.au or +61 3 9545 2176 to request its removal from the dataset. Please note that while CSIRO is able to administer the data housed within this dataset, this control does not extend to the associated publications. Requests to remove publications should be directed to the associated publishing company. Lineage: Original data extracted in 2022 from https://fms05.filemakerstudio.com.au/fmi/webd?homeurl=http://www.monash.edu/#PhytoChem by kind permission of David Collins and Don McGilvery.

The discovery of novel and/or new bioactive natural products from biota sources is often confounded by the reisolation of known natural products. Dereplication strategies that involve the analysis of NMR and MS spectroscopic data to infer structural features present in purified natural products in combination with database searches of these substructures provide an efficient method to rapidly identify known natural products. Unfortunately this strategy has been hampered by the lack of publically available and comprehensive natural product databases and open source cheminformatics tools. A new platform, DEREP-NP, has been developed to help solve this problem. DEREP-NP uses the open source cheminformatics program DataWarrior to generate a database containing counts of 65 structural fragments present in 229 358 natural product structures derived from plants, animals, and microorganisms, published before 2013 and freely available in the nonproprietary Universal Natural Products Database (UNPD). By counting the number of times one or more of these structural features occurs in an unknown compound, as deduced from the analysis of its NMR (1H, HSQC, and/or HMBC) and/or MS data, matching structures carrying the same numeric combination of searched structural features can be retrieved from the database. Confirmation that the matching structure is the same compound can then be verified through literature comparison of spectroscopic data. This methodology can be applied to both purified natural products and fractions containing a small number of individual compounds that are often generated as screening libraries. The utility of DEREP-NP has been verified through the analysis of spectra derived from compounds (and fractions containing two or three compounds) isolated from plant, marine invertebrate, and fungal sources. DEREP-NP is freely available at https://github.com/clzani/DEREP-NP and will help to streamline the natural product discovery process.

Natural products and semi-synthetic compounds continue to be a significant source of drug candidates for a broad range of diseases, including the current pandemic caused by COVID-19. Besides being attractive sources of bioactive compounds for further development or optimization, natural products are excellent candidates of unique substructures for fragment-based drug discovery inspired on natural products. To this end, fragment libraries are required that can be incorporated into automated drug design pipelines. However, it is still scarce to have public fragment libraries based on extensive collections of natural products. Herein we report the generation and analysis of a fragment library of natural products derived from a database with more than 400,000 compounds. We also report fragment libraries of food chemical databases and other compound data sets of interest in drug discovery, including compound libraries relevant for COVID-19 drug discovery. The fragment libraries were characterized in terms of contents and diversity.Sopporting information contains: COCONUT_COMPOUNDS.csv, FooDB_COMPOUNDS.csv, DCM_COMPOUNDS.csv, CAS_COMPOUNDS.csv, 3CLP_COMPOUNDS.csv. All datasets contain the curated structures and the following information: identicator number (ID), simplified molecular input line entry system (Smiles), Average Molecular Weight (AMW), number of carbons, oxygens, nitrogens, heavy atoms, aliphatic rings, aromatic rings, heterocycles, bridgehead atoms, fraction of sp3 carbon atoms and chiral carbons, and a list of fragments generated from each compound. FRAGMENTS_COCONUT.csv, FRAGMENTS_FooDB.csv, FRAGMENTS_DCM.csv, FRAGMENTS_CAS.csv, FRAGMENTS_3CLP.csv. All libraries contain structures generated (Fragments) from each compound library (Dataset) and the following information: number of compounds that contain that fragment in a dataset (Count) and fraction of them (Proportion), average Molecular Weight (AMW), number of carbons, oxygens, nitrogens, heavy atoms, aliphatic rings, aromatic rings, heterocycles, bridgehead atoms, fraction of sp3 carbon atoms and chiral carbons.

Natural product in the COCONUT database with details of source organisms, geolocations and citations.

Natural products derived from bacteria play a pivotal role in drug discovery and utilization. In the past few years, there has been significant interest in pharmaceutical research on the anti-cancer activities of bacteria anti-cancer metabolites (BAMs). However, there are only a few open access databases dedicated to BAMs research. To meet the increasing need for mining and sharing for BAMs-related data resources, this study introduces Microbiota-derived anti-cancer natural products database (MANP), a comprehensive database designed for bacteria anti-cancer natural products based on manually curated data. Currently, MANP contains more than 1000 secondary metabolites with anti-cancer activities, systematic taxonomy and geographical distribution of source bacteria, detailed structure characterization, physico-chemical properties, ADMET information, experimental biological activity data, and accessible literature citations. MANP is an integrated platform for the investigation of bacteria secondary metabolites, discovery of lead compounds, and mining data for structure-activity relationships. Researchers can utilize MANP to explore potential anti-cancer agents derived from bacteria and facilitate the development of novel therapeutic interventions. By providing a comprehensive database of bacterial secondary metabolites, MANP database offers a valuable tool for drug discovery and development in the fight against cancer.

Computer-aided drug design (CADD) often involves virtual screening (VS) of large compound datasets and the availability of such is vital for drug discovery protocols. We assess the bioactivity and “drug-likeness” of a relatively small but structurally diverse dataset (containing >1,000 compounds) from African medicinal plants, which have been tested and proven a wide range of biological activities. The geographical regions of collection of the medicinal plants cover the entire continent of Africa, based on data from literature sources and information from traditional healers. For each isolated compound, the three dimensional (3D) structure has been used to calculate physico-chemical properties used in the prediction of oral bioavailability on the basis of Lipinski’s “Rule of Five”. A comparative analysis has been carried out with the “drug-like”, “lead-like”, and “fragment-like” subsets, as well as with the Dictionary of Natural Products. A diversity analysis has been carried out in comparison with the ChemBridge diverse database. Furthermore, descriptors related to absorption, distribution, metabolism, excretion and toxicity (ADMET) have been used to predict the pharmacokinetic profile of the compounds within the dataset. Our results prove that drug discovery, beginning with natural products from the African flora, could be highly promising. The 3D structures are available and could be useful for virtual screening and natural product lead generation programs.

Natural product in the COCONUT database with details of source organisms, geolocations and citations.

Database for integrating species source of natural products & connecting natural products to biological targets via experimental-derived quantitative activity data.

Abstract

Marine natural products (MNPs) are a vital source of chemical diversity for drug discovery and chemical biology. However, researchers are often hindered by fragmented data sources, proprietary access models, and a lack of tools that support large-scale computational analysis or work in offline environments. We present MarineNP, an open-access database designed to address these challenges. It offers three modes of access: (1) a powerful, web portal for interactive searching and data exportation; (2) complete database downloads in analysis-ready formats (SQL, CSV, RData); and (3) a cross-platform standalone application (Windows, macOS, Linux) that provides the full querying functionality in a fully offline environment. MarineNP improves existing resources by providing meticulously curated data, including taxonomic validation against the World Register of Marine Species (WoRMS) and the inclusion of geolocation information for source organisms. In total, MarineNP currently contains 74,507 unique marine natural products, 10,032 unique source organisms, and 2,653 distinct collection locations.

Availability and Implementation: The MarineNP web server, all data downloads, and the standalone application are freely available to non-commercial users at https://marinenp.scicloud.eu/.

Natural product in the COCONUT database with details of source organisms, geolocations and citations.

Curated database of natural products and their corresponding kingdom classification (e.g. GBIF Backbone Taxonomy, Catalogue of Life) from the LOTUS database (https://lotus.naturalproducts.net/). df_curated.csv data for Github Repository at https://github.com/SIBERanalytics/NPTaxonomy/

ISDB: In Silico DataBase (of Natural Products)

Background

The ISDB repository contains in silico fragmented spectra of natural products, generated using cfm-predict 4 (DOI: 10.1021/acs.analchem.1c01465).

The initial database preparation and its application for dereplication were first described in:
Integration of Molecular Networking and In-Silico MS/MS Fragmentation for Natural Products Dereplication (DOI: 10.1021/acs.analchem.5b04804).

Content

Previous versions of ISDB contained predicted spectra for compounds aggregated within the LOTUS Initiative (DOI: 10.7554/eLife.70780) and included only "merged" spectra.

This version expands beyond taxon-restricted compounds and includes:

• Individual in silico spectra predictions (~1 million)
• Substructure annotations
• Data for compounds from Wikidata and LOTUS

File Structure

.zip Files

Each .zip file contains:

• All original outputs from cfm-predict 4
• Substructure annotations

Wikidata vs LOTUS Files

• Wikidata files: Contain spectra for nearly all compounds found in Wikidata, obtained using this query: https://w.wiki/Cvdo.
• LOTUS files: Contain spectra only for compounds with a "found in taxon" (P703) statement, obtained using this query: https://w.wiki/D35x.

Energy Levels: energyAll vs energySum

• energyAll files: Include spectra for three individual energy levels plus a summed spectrum (4 spectra per polarity per compound).
• energySum files: Contain only the summed spectrum (1 spectrum per polarity per compound).

Related Resources

• Building scripts: https://github.com/mandelbrot-project/spectral_lib_builder
• Matching scripts: https://github.com/mandelbrot-project/spectral_lib_matcher

Natural product in the COCONUT database with details of source organisms, geolocations and citations.

Natural product in the COCONUT database with details of source organisms, geolocations and citations.

Natural product in the COCONUT database with details of source organisms, geolocations and citations.

Additional file 1. Chemical compounds of the Natural Compound Databases (NCDBs).

The Licensed Natural Health Products Database contains information about natural health products that have been issued a product licence by Health Canada. This data extract contains information on NHP Products.

Products with a licence have been assessed by Health Canada and found to be safe, effective and of high quality under their recommended conditions of use. You can identify licensed natural health products by looking for the eight-digit Natural Product Number (NPN) or Homeopathic Medicine Number (DIN-HM) on the label.

An In Silico spectral DataBase (ISDB) of natural products initially calculated from the Universal Natural Products Database (UNPD).

This spectral file is in positive ionisation mode only. Fragmented using cfm-predict 2.0 https://sourceforge.net/projects/cfm-id/

Originally described in Integration of Molecular Networking and In-Silico MS/MS Fragmentation for Natural Products Dereplication https://doi.org/10.1021/ACS.ANALCHEM.5B04804

See http://oolonek.github.io/ISDB/ for associated scripts