standOff. When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote shown on the same row, so the borrowing can be checked against the thing borrowed from without leaving this page. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.| relation to other work | claim_relations | how this paper stands to another: agrees, contradicts, extends, qualifies |
| claim type | claim_type | the shape of the claim: existence, mechanism, method, critique, prediction, null |
| concept edge | concept_edges | an asserted relation between two concepts, with the sentence asserting it |
| concept | concepts | an idea the paper works with, quoted where the paper uses it |
| content tag | content_tags | a finding, definition, quantity, statistic or variable named in the paper |
| contribution | contribution | what the paper claims to add |
| control | controls | an experiment run to eliminate a rival explanation |
| limitation | limitations | what the paper says its evidence cannot support |
| mechanism | mechanisms | how the reported effect is said to come about |
| method | method | how the paper produced its evidence |
| object of study | object_of_study | what the paper is about — the thing it investigates |
| phenomenon | phenomenon | the effect or regularity under study |
| research question | research_question | the question the paper sets itself |
| sense | senses | a distinct use of a term, quoted where the paper fixes it |
| unrecordable relation | unhoused_relations | a relation the paper asserts that this vocabulary cannot express, with the reason |
COCONUT online: Collection of Open Natural Products database
Abstract
contributionclaim_typeconcepts↗concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗sensessensescontent_tagscontent_tags↗content_tags↗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 .
Keywords: Natural products, Database, NoSQL, MongoDB, Molecular similarity search, Molecular substructure search
Introduction
research_questionphenomenonlimitationsconcepts↗concepts↗sensesclaim_relationscontent_tagscontent_tagscontent_tagscontent_tagsNatural products (NPs) have received constant attention from the scientific community due to their relevance in drug discovery, chemical ecology and molecular biology in general. In a recently published review on NPs databases [ 1 ] we inventoried over 120 natural products databases that have been published and used in the last 20 years. However, 16% of these are not available online anymore, 40% are commercial and their content cannot be easily accessed. The open resources are generally either specialized on a particular type of NPs, either lack annotations. For instance, the catalog of NPs from the ZINC database [ 2 ] is composed of over 80,000 entries, some of which can be purchased, but apart from their structure and that they are from natural origin, no additional information is provided. Super Natural II [ 3 ] is considered as the largest among all the NP databases, is accessible online in 2020, but it seems not to be maintained anymore and is mainly composed of compounds that can be purchased. Another recent database, NPAtlas [ 4 ], is constantly growing and extremely well annotated, but it is focusing on microbial NPs only. Another major NPs category, plant-produced compounds, also called phytochemicals, is available in several popular and well maintained databases, such as NuBBEDB [ 5 ], KnapSack [ 6 ], CMAUP [ 7 ] and TCM@Taiwan [ 8 ]. In addition to these relatively big databases, there is a plethora of smaller, more specialized NPs collections, such as FooDB [ 9 ], a user-friendly database hosting a relatively large number of NPs that are found in food. There is, therefore, a need for a generalistic NPs database, that will efficiently aggregate NPs information from various sources, improve its annotation and offer a pleasant user experience. With this ultimate goal in mind, we first assembled the most complete up-to-date COlleCtion of Open Natural ProdUcTs (COCONUT) that we have been continuously curating and annotating. Studies [ 10 , 11 ] showed that fragments from NPs present in COCONUT have high diversity and structural complexity, which makes it, among other possible applications, a suitable source for drug discovery and can be included in drug design pipelines. Our next step was to make this data available to the scientific community as a full-fledged online natural products database, maintained at https://coconut.naturalproducts.net .
concepts↗concepts↗concepts↗sensescontent_tagsThe COCONUT database is free and open to all users and there is no login required to access it. Its web interface allows diverse simple searches (e.g. by molecule name, InChI, InChI key, SMILES, drawn structure, molecular formula), advanced search by molecular features, together with substructure and similarity searches. Users can also download the whole dataset or search results in different formats. The database can be queried programmatically via a REST API, which facilitates COCONUT integration in workflows. The web interface, the back-end and the database are deployed as Docker containers, making it easily portable for hosting other sets of NPs and to be deployed on local installations.
Construction and content
object_of_studymechanisms↗concepts↗unhoused_relationsCOCONUT is assembled from a large number of chemical data sources (Table 1 ), from which NPs have been thoroughly extracted, curated, processed and annotated. The resulting NPs collection is presented within the full-fledged chemical database developed specially for this purpose (Fig. 1 ). Data curation and processing steps, together with the construction of the web interface and the description of available features are described below.
Public databases and datasets from which COCONUT was assembled
Construction and curation of COCONUT online
Data provenance, model and content
claim_relationscontent_tagscontent_tagscontent_tagscontent_tagscontent_tags↗COCONUT data has been extracted from 53 various data sources and several manually collected from literature sets, as shown in Table 1 . In the current COCONUT release (October 2020), there are 406,076 unique “flat” (with no stereochemistry) NPs, and a total of 730,441 NPs where stereochemistry has been preserved when available.
method↗mechanisms↗mechanisms↗controlsconcepts↗concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗unhoused_relationsunhoused_relationsclaim_relationscontent_tagscontent_tagsEvery molecule collected from external sources passed a quality control and a registration procedure, where its structure is checked for size (between 5 and 210 heavy atoms), connectivity (only the biggest connected structure is kept), presence of pseudo-atoms, if implicit and explicit hydrogens are correct, and if the bonds are correct and the valences are conserved. The Kekulé representation is also assigned to the aromatic systems of each compound. At this step, tautomers and ionisation states are standardized following the ChEMBL chemical structure curation pipeline [ 12 ].
mechanisms↗limitationscontrolsconcepts↗concepts↗unhoused_relationssensessensescontent_tagscontent_tags↗content_tags↗Then, NPs from different provenance are unified based on the identity of their InChI keys without stereochemistry. This unification step is performed without stereochemistry, as in different data sources stereochemistry is not systematically present and can also be represented differently. When available, the original molecular structure with stereochemistry is preserved and can be accessed for each NP entry.
limitationslimitationsconcepts↗unhoused_relationscontent_tagsThe authors are well aware that different stereoisomers of a compound can have very different biological activity. The procedure described above was a necessary step to create a unified resource out of distributed databases of varying quality. Further curation will gradually improve stereochemical assignments and linkage to original source articles.
mechanisms↗mechanisms↗limitationsconcepts↗concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗unhoused_relationsconcept_edgescontent_tagscontent_tagscontent_tagsEach unique NP is then assigned a unique identifier, composed of the “CNP” prefix and 7 digits. An automatic curation for NP metadata is performed, comprising the retrieval of its official name, synonyms, cross-references to other major chemical databases. Then, a range of molecular properties, descriptors and fingerprints (full list in Table 2 ) are computed using the in-build CDK [ 13 ] libraries. As the number of the computed properties is quite big (73 fields in each document corresponding to one unique NP), only a selected fraction of them is displayed on the COCONUT web interface. Finally, the first round of automatic curation of NP metadata, in particular the molecular name synonyms, cross-references with other major chemical databases, correction of the literature references (PubMed identifiers and DOIs) and taxonomy is performed. All original data, unified NPs and the derived and calculated information are stored in MongoDB. The chemical classification of all NPs in COCONUT is performed with ClassyFire [ 14 ], and, when available, is displayed in the corresponding section of the compound page. ClassyFire provides a hierarchical chemical classification of chemical compounds and enables grouping NPs by their chemical class. Additionally, frameworks facilitating NPs analyses for their chemical and therapeutic properties are computed for NPs, such as Murcko frameworks [ 15 ], Ertl Functional Groups [ 16 ] and deepSMILES [ 17 ]. DeepSMILES is an adaptation of SMILES for use in deep machine learning of chemical structures. Due to the increased usage of deep learning in chemistry, it is indeed interesting to provide this new chemical representation type pre-computed for NPs.
Molecular features present in COCONUT and in their disponibility in the web interface
mechanisms↗limitationsconcepts↗concepts↗concepts↗unhoused_relationssensesconcept_edgescontent_tagscontent_tags↗content_tagscontent_tagscontent_tags↗Last, the annotation level of each NP in COCONUT is computed. It is a 5-star-based system, where 1 star is the lowest annotation quality (no verified common name, no taxonomic provenance annotation, no literature reference and no trusted data source) and 5 stars is the highest quality, with all the intermediate annotation qualities reflected by 2, 3 and 4 stars. Only ChEBI [ 18 ], KNApSAcK [ 6 ], ChEMBL [ 19 ], CMAUP [ 7 ], NPAtlas [ 4 ] and, of course, the manually picked data are considered as trusted data provenances. For example, caryolivine (CNP0235854) has a 5-stars annotation because it has a verified common name, is known to be produced by Caryomene olivascens , a plant, is associated to a scientific publication and is present in KNApSAcK. The COCONUT NP CNP0330764 has no verified common name, only a computed IUPAC one, but is present in CMAUP and is known to be produced by a range of plants, therefore it’s annotation level is 3. The annotation level is represented with stars on the NP page.
Natural product naming
mechanisms↗concepts↗sensescontent_tagsNPs common names in COCONUT have been retrieved, when available, from their databases of origin. The remaining NPs have been searched by InChI in major chemical databases (PubChem, ChEMBL and ChEBI) and common names and synonyms were retrieved when occurences the compound were found. Additionally to this, IUPAC names were computed for all COCONUT NPs using ChemAxon’s MolCovert [ 20 ], to add nomenclature homogeneity to the dataset. Furthemore, the IUPAC names are used as the main NP name when no official chemical name has been found nor in the original sources, nor by searching big chemical databases. Therefore, all NPs in COCONUT have at least one molecular name.
Computed molecular features
mechanisms↗concepts↗concepts↗concepts↗unhoused_relationscontent_tagscontent_tags↗Figure 2 demonstrates the distributions and relationships of a small selection of computed molecular features within COCONUT. Sugar moieties occur frequently in NPs and have an important impact on their bioactivities and physicochemical properties. However, they are often redundant and therefore obstruct the study of the aglycon. For this reason, NPs in COCONUT have been analysed for sugar moieties presence, and a deglycosylated structure representation was made available in the database. Sugar moieties manipulations were performed using the Sugar Removal Utility [ 21 ]. To track their influence on other features, their absence and presence are colour-mapped (no sugar moiety in the molecular structure in blue, and the presence of at least one sugar moiety in orange). The wide molecular weight range is typical for NPs; it is, however, interesting to notice its correlation with the number of oxygen atoms in the molecule, regardless of the presence and absence of sugar. Another interesting correlation to be noted is between the molecular weight and the nitrogen atom number in sugar-free molecules. The NP-likeness score [ 22 ], trained on high-quality NPs dataset and computed with NaPLeS [ 23 ], which was trained on high-quality NPs dataset, has a typical distribution for an NPs set, where most molecules have a positive score.
Pair plot of a selection of five of the molecular features available in COCONUT. Colour mapping corresponds to the presence (yellow) and absence (blue) of glycosidic moieties in the molecular structures of the NPs in COCONUT
mechanisms↗limitationscontrolsconcepts↗concepts↗concepts↗unhoused_relationssensesconcept_edgescontent_tagscontent_tagscontent_tags↗At this point, an additional NPs curation step has been performed, due to the possible inconsistency in genuine NPs of one of the used sources, SuperNatural II. NPs that are not occuring in other datasets used to assemble COCONUT, but only in SuperNatural II, have been thoroughly tested. To be kept in COCONUT and be considered as a genuine or predicted NP, such a molecule has to have a strictly positive NP-likeness score, be classified as a NP by NPclassifier [ 24 ], a deep neural network-based structural classification tool specialised in NPs or have a sugar moiety in its structure. The 24,880 molecules from SuperNatural II that didn’t pass this additional quality control have been removed from COCONUT, until further proof of their natural provenance.
limitationsCounting rings in a molecule can become a complex task, as the outer perimeter of two fused rings can be counted as one big ring. With more condensed rings, the number of fused ring perimeters (aka as the set of all rings) can grow steeply. In Fig. 2 , only the minimal ring count (the minimal cycle base) is represented.
Natural product annotation
limitationslimitationsconcepts↗concepts↗concepts↗concepts↗unhoused_relationsunhoused_relationscontent_tagscontent_tagscontent_tagscontent_tagscontent_tagscontent_tagscontent_tagscontent_tags↗content_tags↗The particularity of NPs, opposed to synthetic molecules, which constitute the biggest part of chemical databases, resides in their production by living organisms. Therefore, in addition to their structure and computable structural properties, NPs need to be annotated with at least one literature reference, mentioning where, when and from which organism the NP was isolated. As a direct consequence, an NP entry should be associated with at least one organism, preferentially with an NCBI taxonomy identifier and the geographic location where the organism is naturally occuring or has been collected. Regrettably, this metadata is often omitted in public databases from which COCONUT was assembled. Therefore, only 31.5% (134,379) of NPs in COCONUT are annotated with at least one organism taxa, for 15.4% (66,068) of NPs the geographic location (on the continent level) of the organism occurence or collection is known and only 16.6% (70,730) of NPs have at least one literature reference. These numbers combine both the retrieval of the original NP annotations from their sources and our efforts to retrieve more extensive information from major trusted chemical databases, PubChem [ 25 ], ChEMBL [ 19 ], ChEBI [ 18 ], CMAUP [ 7 ] and KnapSacK [ 6 ]. Despite our efforts, most of the links between the original publication of the structure elucidation of an NP and its reference, source organism and its geographical location are still missing. A possible solution to fill these gaps is manual curation, but the amount of data in COCONUT is redhibitory for even considering this approach. Another solution is to use unsupervised machine learning for optical recognition approaches, to parse modern peer-reviewed literature and books to re-establish links between NPs structures and their provenance.
limitationsunhoused_relationssensescontent_tagscontent_tagscontent_tagsWe analysed the taxonomic classification of known NPs producers together with overlaps in NPs production between superkingdom for the 31% of the NPs in COCONUT for which the provenance organism is known (Fig. 3 ). Here are distinguished five taxonomic categories: plants, bacteria, fungi, animals and marine. The last one is not a proper monoclade classification, but rather reflects a group of organisms that are found only in marine and oceanic environments, and therefore can overlap in terms of its species and NP content with other categories, which are more stringent taxonomically. A large part (65%) of these annotated NPs are produced only by plants, and only very few (0.5%) are from animal origin. Main overlaps in terms of NP production between the taxonomic kingdoms are between plants and marine organisms (which is unsurprising, as there can be real plants among the marine entities) and surprisingly between plants and fungi. The other overlaps between taxonomic kingdoms are not as significant. It needs to be pointed out here that multicellular organisms, such as plants, animals and some of the fungi are most of the time in symbiosis with microorganisms, in particular bacteria. Therefore, NPs isolated from such a multicellular organism can be synthesized and secreted by their symbionts or microbiomes, and therefore mistakenly assigned to an incorrect organism.
Overlap of NPs taxonomic provenance in COCONUT
limitationsunhoused_relationssensesThe geographic location of the collection or the natural presence of the NP-producing organism is a piece of information that is even more difficult to obtain. Nowadays, a range of organisms, and in particular plants, can be found in different parts of the planet due to globalisation and their success in human consumption (e.g. garlic, tomatoes, curcuma or ginger). It is, therefore, difficult, if not impossible, to determine their original provenance. Also, the geographical information is often omitted in literature and most NPs databases. When available, the geographical provenance is stored in the MongoDB dump of COCONUT, but not displayed on the website.
limitationsFor NPs where geographical information is available, it appears that most of them are produced by organisms that have been isolated in Asia (Fig. 4 ). This bias is introduced by the intensive study by scientists of the traditional Chinese and Indian medicines and by the big efforts in isolation and elucidation of NPs from medicinal plants. NPs from the African continent are also well represented in COCONUT (Fig. 4 ), mainly due to the scientific interest in African traditional medicines and African biodiversity. There is, for now, no data from the biodiversity of the Australian continent, and only very little data for NPs isolated from endemic European organisms. NPs from the Americas are mainly extracted and solved while Brazilian and Mexican biodiversity exploration. Only a few NPs are present in more than one continent, mainly in Asia and Africa, and the overlap values are biased by the very different NPs set sizes between the different continents.
Overlap of NPs geographic provenance in COCONUT
Web interface and technical specificities
mechanisms↗concepts↗concept_edgesAll COCONUT data is stored with MongoDB, a cross-platform document-oriented NoSQL database program. The smallest unit in MongoDB is a document, composed of key and value pairs that are similar to JSON objects. Documents of the same nature are organized in collections, which are the equivalent of the SQL-based databases tables. MongoDB is particularly adapted to big and complex data, supports multiple indexing, including text indexing allowing enhanced text search in text-indexed fields and contains a wide range of in-build search and analysis functions.
concepts↗concepts↗concept_edgesconcept_edgescontent_tagscontent_tags↗content_tags↗Two major collections are present in the COCONUT database: SourceNaturalProduct, which contains the original NPs data collected from the open sources, and UniqueNaturalProduct, the unified and curated collection of NPs. The full version of COCONUT with all the calculated features can be accessed as a MongoDB dump in the Downloads section of the website. Requests for displaying additional crucial features in the web interface and making them searchable through the advanced search interface are welcome via the COCONUT GitHub tracker (see below).
concepts↗concepts↗concepts↗concepts↗concepts↗concepts↗content_tagsThe COCONUT online front-end is developed entirely with React.js [ 26 ], a JavaScript library to build responsive and efficient user interfaces. The OpenChemLib library [ 27 ] is used to handle the chemical editor for the search functions. The COCONUT back-end, allowing to process the front-end requests and to communicate with the database is written in Kotlin and Java 11 using the Spring framework. The CDK [ 13 ] library is used to process chemical information and formats.
unhoused_relationscontent_tagsCOCONUT web interface, back-end and database are entirely Dockerised, allowing a quick and easy deployment on local servers and cloud. All the code, for both front-end and back-end, is available on GitHub ( https://github.com/mSorok/NaturalProductsOnline ).
Searching the database
COCONUT online has been developed to be a full-fledged chemical database and in particular to fit the NPs structural and annotational particularities, with all the subsequent functions. At the moment, the chemical search is uncommon with MongoDB, therefore several approaches have been implemented to run molecular substructure and similarity searches.
Simple search
mechanisms↗concepts↗concepts↗unhoused_relationssensescontent_tagscontent_tags↗The so-called “simple” search can be performed using the header search bar. The users can enter there molecule names (e.g. “curcumin”), SMILES, InChI, InChi key, COCONUT ids and molecular formulas. Name search uses native MongoDB text indexing, allowing fuzzy, flexible search in the “name” and “synonyms” fields. The input string type is first identified using regular expressions, then the DB is queried against the appropriate fields, and the result, when exists, is returned to the front-end.
Substructure search implementation
mechanisms↗mechanisms↗controlsconcepts↗concepts↗concepts↗concepts↗concepts↗unhoused_relationssensescontent_tagscontent_tags↗content_tags↗Searching for an exact substructure in a MongoDB database of molecules appears to be surprisingly easy. Each molecule in the database needs to have their fingerprints of choice (in COCONUT are used the PubChem fingerprints) to be precomputed and stored as a list of bytes (BinData type in MongoDB). The query molecule (substructure) then needs to have its fingerprint to be also computed and to be matched against the database using the $allBitsSet function [ 28 ]. This native to MongoDB function allows to select documents in a collection where a BinData field has all the query bits set to “on” (but can have bits set to “on” that are not present in the query). To confirm the substructure match, the user can select between the default Ullmann [ 29 ], the Vento-Foggia [ 30 ] and the depth-first (DF) [ 31 ] pattern matching approaches, all performed using the CDK in-build algorithms. These three pattern matching techniques tend to, generally, return very similar results, the difference between them lying rather in their approach to matching substructures, therefore the usage of the default, Ullmann, method is to be privileged by users unfamiliar with the intricacies of such matching.
Similarity search implementation
mechanisms↗concepts↗claim_relationscontent_tagsSimilarity search with MongoDB was implemented following the excellent ChEBML blog post on LSH-based similarity search in MongoDB [ 32 ] and adapted to Java, Kotlin and Spring data. In this approach, the MongoDB aggregation framework is used to perform inverted indexing search against PubChem fingerprints stored in a separate table and referencing COCONUT identifiers that contain the molecular features encoded by each bit.
Advanced search
concepts↗unhoused_relationscontent_tags↗The advanced search supports searching for NPs in COCONUT according to a range of parameters, such as molecular formula, molecular descriptor values, number of rings, type of sugar moieties present in them, etc.
Querying COCONUT through the API
mechanisms↗unhoused_relationssensescontent_tags↗A REST API has been developed for COCONUT online in order to permit programmatic querying and facilitate its integration in workflows. It relies on Kotlin API functionalities and it’s usage, together with some examples, is described in detail in the documentation section of the website ( https://coconut.naturalproducts.net/documentation ).
Documentation
Complete documentation describing COCONUT, its data and functionalities are available at the documentation section of the website https://coconut.naturalproducts.net/documentation .
Utility and discussion
The online COCONUT database is an open tool for researchers in the natural products community. COCONUT is the biggest collection of NPs in 2020 and the data it contains already benefits researchers in NPs with various aims, such as biodiversity research and drug discovery. The web interface allows querying and parsing the data collection in various, chemically relevant ways with adequate performance. It is also the first big chemical database using MongoDB as a storage management system.
A wide range of molecular descriptors are pre-computed and literature, producer taxonomy and their geography are as much annotated as currently possible without extensive manual curation. The web database can be searched in multiple ways, by molecular structure, by compound name and by molecular features, making this repository a complete chemical database. The user interface is modern and easy to use. Besides, the whole content of COCONUT is available for download in multiple formats.
In the close future, COCONUT will support user registration to enable user-driven NPs curation and submission and will undergo a better data annotation, in particular regarding the organisms that are producing the NPs, their geography and the corresponding literature, using deep learning approaches.
Feedback
Bugs, annotation issues and requests of new COCONUT entries or re-annotation of existing ones can be reported at the project issues tracker ( https://github.com/mSorok/NaturalProductsOnline/issues ). Suggestions for new features are also welcome.
Availability
content_tagsAll COCONUT data, code to process raw NPs data, data quality control and annotation, and the code for the font- and the back-end of the COCONUT online website are freely available without any restriction. The latest COCONUT data, as MongoDB full dump can be downloaded at https://coconut.naturalproducts.net/download . Code for data assembly, processing and quality control process codes is available on GitHub at https://github.com/mSorok/COCONUT . The code for the front-end and back-end is also available on GitHub at https://github.com/mSorok/NaturalProductsOnline .
Conclusions
COCONUT is the largest open collection of elucidated and predicted NPs at this time. It has a great potential of being of particular importance for the NPs research community as it gathers most of open NPs knowledge in one single place, and makes it easily accessible and queryable.
limitationsThe final aim of COCONUT is to provide to the scientific community NPs structures and their provenance, i.e.. organisms that synthesize them and geographic location of the latter. However, a lot of data curation, in particular using new generation deep learning-based methods of extracting information from publications and books, together with website functionalities developments are still need to be done for COCONUT, but the database as it is now is already an important tool to facilitate NPs and medicinal chemistry research.
Acknowledgements
Not applicable.
Abbreviations
Natural products
COlleCtion of Open Natural ProdUcTs
Chemistry Development Kit
International Union of Pure and Applied Chemistry
Application Programming Interface
REpresentational State Transfer
Digital Object Identifier
JavaScript Object Notation
(non-/not only) Structured Query Language
Authors’ contributions
MS coordinated the study, participated in the implementation of the front-end and the backend, collected; processed and curated the COCONUT data and wrote the manuscript. PM participated in the implementation of the front-end and the back-end of COCONUT online. KR and MAY helped with COCONUT data curation. KR designed the COCONUT logo. CS designed and supervised the study. All authors read and approved the final manuscript.
Funding
Open Access funding enabled and organized by Projekt DEAL. This work was supported by the German Research Foundation within the framework CRC1127 ChemBioSys.
Availability of data and materials
the source code of the web interface and the back-end is available on GitHub at https://github.com/mSorok/NaturalProductsOnline . The data was curated and processed using the COCONUT code suite available on GitHub at https://github.com/mSorok/COCONUT . All COCONUT data can be accessed on the website at https://coconut.naturalproducts.net/ and downloaded entirely or partially in several formats (MongoDB dump, SDF and SMI (SMILES)).
Competing interests
The authors declare no competing interests.
Footnotes
Contributor Information
Maria Sorokina, Email: maria.sorokina@uni-jena.de.
Peter Merseburger, Email: peter.merseburger@uni-jena.de.
Kohulan Rajan, Email: kohulan.rajan@uni-jena.de.
Mehmet Aziz Yirik, Email: yirik.mehmetaziz@uni-jena.de.
Christoph Steinbeck, Email: christoph.steinbeck@uni-jena.de.
References
Associated Data
Data Availability Statement
the source code of the web interface and the back-end is available on GitHub at https://github.com/mSorok/NaturalProductsOnline . The data was curated and processed using the COCONUT code suite available on GitHub at https://github.com/mSorok/COCONUT . All COCONUT data can be accessed on the website at https://coconut.naturalproducts.net/ and downloaded entirely or partially in several formats (MongoDB dump, SDF and SMI (SMILES)).
Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; 6 of 6 relations here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.
| facet | tag | field | conf. | whose words |
|---|---|---|---|---|
| object_of_study | the aggregation, curation, annotation, storage, and online retrieval of open natural-product structures and provenance | object_of_study | the paper's words | |
| research_question | whether distributed open natural-product collections can be unified into a general, freely accessible database that supports chemical and programmatic search | research_question | the paper's words | |
| contribution | the COCONUT aggregated dataset, its chemical and provenance curation pipeline, and a searchable, downloadable, containerized web database with a REST API | contribution | the paper's words | |
| claim_type | existence | claim_type | the paper's words | |
| phenomenon | fragmented natural-product knowledge, heterogeneous molecular representations, incomplete provenance metadata, and chemical retrieval across a large unified collection | phenomenon | the paper's words | |
| method | system-or-tool-building also in: system-or-tool-building | method | the paper's words | |
| mechanisms | Extracts, curates, processes, and annotates natural products from many chemical sources. also in: source aggregation | mechanisms[0] | 0.95 | the tagger's words |
| mechanisms | Checks size, connectivity, pseudo-atoms, hydrogens, bonds, and valence before registration. also in: structural quality control | mechanisms[1] | 0.95 | the tagger's words |
| mechanisms | Normalizes tautomer and ionization states using an established chemical-curation pipeline. also in: ChEMBL standardization | mechanisms[2] | 0.95 | the tagger's words |
| mechanisms | Collapses records across sources without relying on inconsistently supplied stereochemistry. also in: InChIKey unification | mechanisms[3] | 0.95 | the tagger's words |
| mechanisms | Retrieves names, synonyms, cross-references, literature identifiers, and taxonomy. also in: automatic metadata curation | mechanisms[4] | 0.95 | the tagger's words |
| mechanisms | Assigns hierarchical chemical classes that enable class-based grouping. also in: ClassyFire | mechanisms[5] | 0.95 | the tagger's words |
| mechanisms | Summarizes the presence of verified names, taxonomy, literature, and trusted provenance. also in: five-star annotation score | mechanisms[6] | 0.95 | the tagger's words |
| mechanisms | Combines original names, InChI searches in major databases, and computed IUPAC names. also in: name resolution | mechanisms[7] | 0.95 | the tagger's words |
| mechanisms | Detects sugar moieties and provides a deglycosylated representation. also in: Sugar Removal Utility | mechanisms[8] | 0.95 | the tagger's words |
| mechanisms | Retains source-only molecules only when at least one natural-product plausibility test passes. also in: SuperNatural II provenance screen | mechanisms[9] | 0.95 | the tagger's words |
| mechanisms | Stores complex records and supplies indexing, text search, and aggregation functions. also in: MongoDB document storage | mechanisms[10] | 0.95 | the tagger's words |
| mechanisms | Identifies a simple-search input type before querying the corresponding database field. also in: regular-expression routing | mechanisms[11] | 0.95 | the tagger's words |
| mechanisms | Uses all query bits to select candidate structures before exact pattern matching. also in: fingerprint prefilter | mechanisms[12] | 0.95 | the tagger's words |
| mechanisms | Confirms substructure candidates with Ullmann, Vento-Foggia, or depth-first matching. also in: CDK pattern matching | mechanisms[13] | 0.95 | the tagger's words |
| mechanisms | Maps PubChem fingerprint bits to COCONUT identifiers for LSH-based similarity retrieval. also in: inverted fingerprint index | mechanisms[14] | 0.95 | the tagger's words |
| mechanisms | Exposes programmatic queries for integrating COCONUT into external workflows. also in: REST API | mechanisms[15] | 0.95 | the tagger's words |
| limitations | Many existing natural-product databases are offline, commercial, narrowly specialized, or poorly annotated. | limitations[0] | 0.95 | the tagger's words |
| limitations | Source databases vary in whether and how stereochemistry is represented. | limitations[1] | 0.95 | the tagger's words |
| limitations | Unifying without stereochemistry can merge stereoisomers with very different biological activities. | limitations[2] | 0.95 | the tagger's words |
| limitations | The source-integration procedure reflects distributed databases of varying quality. | limitations[3] | 0.95 | the tagger's words |
| limitations | Only a selected subset of the 73 computed fields is displayed in the web interface. | limitations[4] | 0.95 | the tagger's words |
| limitations | Common names, taxonomic provenance, literature references, and trusted sources are absent from low-quality records. | limitations[5] | 0.95 | the tagger's words |
| limitations | One contributing source required additional screening because its records had uncertain natural-product status. | limitations[6] | 0.95 | the tagger's words |
| limitations | Ring counts can be ambiguous for fused and condensed ring systems. | limitations[7] | 0.95 | the tagger's words |
| limitations | Most records still lack links among original publications, structures, organisms, and geography. | limitations[8] | 0.95 | the tagger's words |
| limitations | The scale of COCONUT makes comprehensive manual curation infeasible. | limitations[9] | 0.95 | the tagger's words |
| limitations | Organism provenance may be misassigned when symbionts or microbiomes produce an isolated molecule. | limitations[10] | 0.95 | the tagger's words |
| limitations | Global movement of organisms and omission in literature make original geographic provenance difficult or impossible to infer. | limitations[11] | 0.95 | the tagger's words |
| limitations | Geographic coverage is biased by uneven research attention and dataset sizes. | limitations[12] | 0.95 | the tagger's words |
| limitations | Further annotation and functionality development remain necessary, especially for organisms, geography, and literature links. | limitations[13] | 0.95 | the tagger's words |
| controls | structure-size, connectivity, atom, hydrogen, bond, and valence checks eliminates: invalid or unsupported external structures entering registration unchecked · outcome: held | controls[0] | 0.95 | the tagger's words |
| controls | stereochemistry-free identity plus preservation of original stereochemical structures eliminates: inconsistent source stereochemistry preventing flat-record unification while discarding all source detail · outcome: held | controls[1] | 0.95 | the tagger's words |
| controls | additional filtering only for SuperNatural II-exclusive records eliminates: questionable source-specific natural-product assignments contaminating the integrated collection · outcome: held | controls[2] | 0.95 | the tagger's words |
| controls | fingerprint all-bits-set prefilter followed by exact CDK graph matching eliminates: treating fingerprint containment alone as a confirmed substructure · outcome: held | controls[3] | 0.95 | the tagger's words |
| concepts | Natural products also in: Natural products | concepts[0] | 0.95 | the paper's words |
| concepts | small molecules also in: small molecules | concepts[1] | 0.95 | the paper's words |
| concepts | living organisms also in: living organisms | concepts[2] | 0.95 | the paper's words |
| concepts | bioactive also in: bioactive | concepts[3] | 0.95 | the paper's words |
| concepts | COCONUT also in: COCONUT | concepts[4] | 0.95 | the paper's words |
| concepts | aggregated dataset also in: aggregated dataset | concepts[5] | 0.95 | the paper's words |
| concepts | elucidated and predicted NPs also in: elucidated and predicted NPs | concepts[6] | 0.95 | the paper's words |
| concepts | web interface also in: web interface | concepts[7] | 0.95 | the paper's words |
| concepts | generalistic NPs database also in: generalistic NPs database | concepts[8] | 0.95 | the paper's words |
| concepts | drug discovery also in: drug discovery | concepts[9] | 0.95 | the paper's words |
| concepts | REST API also in: REST API | concepts[10] | 0.95 | the paper's words |
| concepts | Docker containers also in: Docker containers | concepts[11] | 0.95 | the paper's words |
| concepts | chemical data sources also in: chemical data sources | concepts[12] | 0.95 | the paper's words |
| concepts | quality control also in: quality control | concepts[13] | 0.95 | the paper's words |
| concepts | registration procedure also in: registration procedure | concepts[14] | 0.95 | the paper's words |
| concepts | heavy atoms also in: heavy atoms | concepts[15] | 0.95 | the paper's words |
| concepts | biggest connected structure also in: biggest connected structure | concepts[16] | 0.95 | the paper's words |
| concepts | tautomers also in: tautomers | concepts[17] | 0.95 | the paper's words |
| concepts | ionisation states also in: ionisation states | concepts[18] | 0.95 | the paper's words |
| concepts | ChEMBL chemical structure curation pipeline | concepts[19] | 0.95 | the paper's words |
| concepts | InChI keys without stereochemistry also in: InChI keys without stereochemistry | concepts[20] | 0.95 | the paper's words |
| concepts | stereochemistry also in: stereochemistry | concepts[21] | 0.95 | the paper's words |
| concepts | stereoisomers also in: stereoisomers | concepts[22] | 0.95 | the paper's words |
| concepts | unique identifier also in: unique identifier | concepts[23] | 0.95 | the paper's words |
| concepts | molecular properties also in: molecular properties | concepts[24] | 0.95 | the paper's words |
| concepts | descriptors also in: descriptors | concepts[25] | 0.95 | the paper's words |
| concepts | fingerprints also in: fingerprints | concepts[26] | 0.95 | the paper's words |
| concepts | MongoDB also in: MongoDB | concepts[27] | 0.95 | the paper's words |
| concepts | ClassyFire also in: ClassyFire | concepts[28] | 0.95 | the paper's words |
| concepts | hierarchical chemical classification also in: hierarchical chemical classification | concepts[29] | 0.95 | the paper's words |
| concepts | Murcko frameworks also in: Murcko frameworks | concepts[30] | 0.95 | the paper's words |
| concepts | Ertl Functional Groups also in: Ertl Functional Groups | concepts[31] | 0.95 | the paper's words |
| concepts | deepSMILES also in: deepSMILES | concepts[32] | 0.95 | the paper's words |
| concepts | adaptation of SMILES also in: adaptation of SMILES | concepts[33] | 0.95 | the paper's words |
| concepts | annotation level also in: annotation level | concepts[34] | 0.95 | the paper's words |
| concepts | 5-star-based system also in: 5-star-based system | concepts[35] | 0.95 | the paper's words |
| concepts | trusted data provenances also in: trusted data provenances | concepts[36] | 0.95 | the paper's words |
| concepts | IUPAC names also in: IUPAC names | concepts[37] | 0.95 | the paper's words |
| concepts | Sugar Removal Utility also in: Sugar Removal Utility | concepts[38] | 0.95 | the paper's words |
| concepts | deglycosylated structure representation | concepts[39] | 0.95 | the paper's words |
| concepts | NP-likeness score also in: NP-likeness score | concepts[40] | 0.95 | the paper's words |
| concepts | NPclassifier also in: NPclassifier | concepts[41] | 0.95 | the paper's words |
| concepts | deep neural network-based structural classification tool | concepts[42] | 0.95 | the paper's words |
| concepts | genuine or predicted NP also in: genuine or predicted NP | concepts[43] | 0.95 | the paper's words |
| concepts | literature reference also in: literature reference | concepts[44] | 0.95 | the paper's words |
| concepts | NCBI taxonomy identifier also in: NCBI taxonomy identifier | concepts[45] | 0.95 | the paper's words |
| concepts | geographic location also in: geographic location | concepts[46] | 0.95 | the paper's words |
| concepts | manual curation also in: manual curation | concepts[47] | 0.95 | the paper's words |
| concepts | document-oriented NoSQL database program | concepts[48] | 0.95 | the paper's words |
| concepts | SourceNaturalProduct also in: SourceNaturalProduct | concepts[49] | 0.95 | the paper's words |
| concepts | UniqueNaturalProduct also in: UniqueNaturalProduct | concepts[50] | 0.95 | the paper's words |
| concepts | React.js also in: React.js | concepts[51] | 0.95 | the paper's words |
| concepts | OpenChemLib also in: OpenChemLib | concepts[52] | 0.95 | the paper's words |
| concepts | Kotlin also in: Kotlin | concepts[53] | 0.95 | the paper's words |
| concepts | Java 11 also in: Java 11 | concepts[54] | 0.95 | the paper's words |
| concepts | Spring framework also in: Spring framework | concepts[55] | 0.95 | the paper's words |
| concepts | CDK also in: CDK | concepts[56] | 0.95 | the paper's words |
| concepts | simple searches also in: simple searches | concepts[57] | 0.95 | the paper's words |
| concepts | text indexing also in: text indexing | concepts[58] | 0.95 | the paper's words |
| concepts | regular expressions also in: regular expressions | concepts[59] | 0.95 | the paper's words |
| concepts | PubChem fingerprints also in: PubChem fingerprints | concepts[60] | 0.95 | the paper's words |
| concepts | $allBitsSet function also in: $allBitsSet function | concepts[61] | 0.95 | the paper's words |
| concepts | Ullmann also in: Ullmann | concepts[62] | 0.95 | the paper's words |
| concepts | Vento-Foggia also in: Vento-Foggia | concepts[63] | 0.95 | the paper's words |
| concepts | depth-first (DF) also in: depth-first (DF) | concepts[64] | 0.95 | the paper's words |
| concepts | LSH-based similarity search also in: LSH-based similarity search | concepts[65] | 0.95 | the paper's words |
| concepts | advanced search also in: advanced search | concepts[66] | 0.95 | the paper's words |
| unhoused_relations | distributed open data sources → COCONUT COCONUT aggregates natural-product records from many open chemical sources. | unhoused_relations[0] | 0.95 | the tagger's words |
| unhoused_relations | structural quality control → registered molecules Every collected molecule passes structural checks before registration. | unhoused_relations[1] | 0.95 | the tagger's words |
| unhoused_relations | ChEMBL chemical structure curation pipeline → tautomers and ionisation states COCONUT follows the ChEMBL pipeline to standardize tautomer and ionization states. | unhoused_relations[2] | 0.95 | the tagger's words |
| unhoused_relations | InChI keys without stereochemistry → unified natural-product records Records from different sources are unified under stereochemistry-free InChIKey identity. | unhoused_relations[3] | 0.95 | the tagger's words |
| unhoused_relations | stereochemistry-free unification → stereoisomer-specific biological activity The necessary unification policy does not preserve stereoisomer distinctions in flat records. | unhoused_relations[4] | 0.95 | the tagger's words |
| unhoused_relations | automatic metadata curation → names, cross-references, literature, and taxonomy Automatic curation retrieves and corrects multiple metadata classes. | unhoused_relations[5] | 0.95 | the tagger's words |
| unhoused_relations | trusted data provenance → annotation stars Trusted source membership contributes to a higher annotation-quality score. | unhoused_relations[6] | 0.95 | the tagger's words |
| unhoused_relations | Sugar Removal Utility → deglycosylated structure representation Sugar-moiety manipulation supplies a deglycosylated representation. | unhoused_relations[7] | 0.95 | the tagger's words |
| unhoused_relations | additional SuperNatural II quality control → 24880 source-only molecules The additional screen removed molecules lacking any accepted natural-product signal. | unhoused_relations[8] | 0.95 | the tagger's words |
| unhoused_relations | missing source metadata → incomplete natural-product provenance Omitted organism, geography, and literature links leave most records incompletely annotated. | unhoused_relations[9] | 0.95 | the tagger's words |
| unhoused_relations | COCONUT dataset scale → manual curation The amount of data makes exhaustive manual curation infeasible. | unhoused_relations[10] | 0.95 | the tagger's words |
| unhoused_relations | symbionts and microbiomes → organism attribution Compounds made by symbionts can be mistakenly assigned to the sampled host organism. | unhoused_relations[11] | 0.95 | the tagger's words |
| unhoused_relations | globalisation and omitted location data → original geographic provenance Organism movement and missing literature metadata make original provenance difficult to determine. | unhoused_relations[12] | 0.95 | the tagger's words |
| unhoused_relations | simple searches → COCONUT COCONUT exposes simple searches over names and chemical identifiers. | unhoused_relations[13] | 0.95 | the tagger's words |
| unhoused_relations | advanced search → COCONUT COCONUT exposes advanced search over molecular properties. | unhoused_relations[14] | 0.95 | the tagger's words |
| unhoused_relations | PubChem fingerprint prefilter → exact substructure candidates The all-bits-set query selects candidates that are then confirmed by graph matching. | unhoused_relations[15] | 0.95 | the tagger's words |
| unhoused_relations | REST API → external workflows Programmatic querying facilitates integration of COCONUT in workflows. | unhoused_relations[16] | 0.95 | the tagger's words |
| unhoused_relations | Dockerisation → local and cloud deployment Containerization permits rapid deployment on local servers and cloud infrastructure. | unhoused_relations[17] | 0.95 | the tagger's words |
| senses | natural product as a small molecule produced by a living organism | senses[0] | 0.95 | the tagger's words |
| senses | COCONUT as both an aggregated dataset and an online access system | senses[1] | 0.95 | the tagger's words |
| senses | generalist database as an integrator across thematic collections | senses[2] | 0.95 | the tagger's words |
| senses | open access as no-login browsing plus downloadable data and unrestricted code | senses[3] | 0.95 | the tagger's words |
| senses | flat natural-product identity as InChIKey equality without stereochemistry | senses[4] | 0.95 | the tagger's words |
| senses | stereochemistry as preserved source information rather than the unification key | senses[5] | 0.95 | the tagger's words |
| senses | annotation quality as metadata completeness and trusted provenance rather than chemical validity alone | senses[6] | 0.95 | the tagger's words |
| senses | computed IUPAC name as a fallback when no official or common name is found | senses[7] | 0.95 | the tagger's words |
| senses | NP-likeness as a plausibility feature rather than proof of natural provenance | senses[8] | 0.95 | the tagger's words |
| senses | marine as an environmental grouping rather than a monoclade taxon | senses[9] | 0.95 | the tagger's words |
| senses | geographic provenance as occurrence or collection location rather than necessarily evolutionary origin | senses[10] | 0.95 | the tagger's words |
| senses | simple search as input-type dispatch across heterogeneous identifier fields | senses[11] | 0.95 | the tagger's words |
| senses | substructure match as fingerprint screening followed by exact graph confirmation | senses[12] | 0.95 | the tagger's words |
| senses | REST API as workflow integration rather than only interactive web access | senses[13] | 0.95 | the tagger's words |
| claim_relations | contrasts-with → specialized, commercial, unavailable, or sparsely annotated natural-product databases note: The contribution is motivated against the fragmented database landscape. | claim_relations[0] | 0.95 | the tagger's words |
| claim_relations | builds-on → 53 open data sources and manually collected literature sets note: The new collection directly aggregates these sources. | claim_relations[1] | 0.95 | the tagger's words |
| claim_relations | builds-on → the ChEMBL chemical structure curation pipeline note: Tautomer and ionization-state standardization explicitly follows ChEMBL. | claim_relations[2] | 0.95 | the tagger's words |
| claim_relations | builds-on → LSH-based similarity search in MongoDB note: The implementation adapts the cited MongoDB similarity-search design. | claim_relations[3] | 0.95 | the tagger's words |
| concept_edges | MongoDB —is-a→ document-oriented NoSQL database program the relation itself is separately evidenced · strength of the relation: 1 · note: Direct categorical definition. · the relation stated: MongoDB is described as a document-oriented NoSQL database program. also in: MongoDB · document-oriented NoSQL database program | concept_edges[0] | 0.95 | the tagger's words |
| concept_edges | SourceNaturalProduct —part-of→ COCONUT the relation itself is separately evidenced · strength of the relation: 1 · note: Explicit component membership. · the relation stated: SourceNaturalProduct is one of COCONUT's two major database collections. also in: SourceNaturalProduct · COCONUT | concept_edges[1] | 0.95 | the tagger's words |
| concept_edges | UniqueNaturalProduct —part-of→ COCONUT the relation itself is separately evidenced · strength of the relation: 1 · note: Explicit component membership. · the relation stated: UniqueNaturalProduct is one of COCONUT's two major database collections. also in: UniqueNaturalProduct · COCONUT | concept_edges[2] | 0.95 | the tagger's words |
| concept_edges | NPclassifier —is-a→ deep neural network-based structural classification tool the relation itself is separately evidenced · strength of the relation: 1 · note: Direct categorical definition. · the relation stated: NPclassifier is explicitly described as a deep neural network-based structural classification tool. | concept_edges[3] | 0.95 | the tagger's words |
| concept_edges | deepSMILES —is-a→ adaptation of SMILES the relation itself is separately evidenced · strength of the relation: 1 · note: Direct categorical definition. · the relation stated: DeepSMILES is explicitly described as an adaptation of SMILES. also in: deepSMILES · adaptation of SMILES | concept_edges[4] | 0.95 | the tagger's words |
| concept_edges | annotation level —is-a→ 5-star-based system the relation itself is separately evidenced · strength of the relation: 1 · note: Direct categorical definition. · the relation stated: The annotation level is a 5-star-based system. also in: annotation level · 5-star-based system | concept_edges[5] | 0.95 | the tagger's words |
| content_tags | COCONUT aggregates elucidated and predicted natural products from open sources and provides a web interface for browsing, searching, and downloading them. | content_tags.findings[0] | 0.95 | the tagger's words |
| content_tags | The database addresses a landscape of more than 120 published natural-product databases, including unavailable, commercial, specialized, and sparsely annotated resources. | content_tags.findings[1] | 0.95 | the tagger's words |
| content_tags | COCONUT requires no login and supports simple, advanced, substructure, similarity, and programmatic searches. | content_tags.findings[2] | 0.95 | the tagger's words |
| content_tags | The October 2020 release contains 406,076 unique flat natural products and 730,441 stereochemistry-preserved records. | content_tags.findings[3] | 0.95 | the tagger's words |
| content_tags | Every external molecule passes structural quality control and ChEMBL-style tautomer and ionization-state standardization. | content_tags.findings[4] | 0.95 | the tagger's words |
| content_tags | Records from different sources are unified by InChIKey identity without stereochemistry while original stereochemical structures are retained when available. | content_tags.findings[5] | 0.95 | the tagger's words |
| content_tags | The unification policy trades stereoisomer specificity for integration across sources of varying quality. | content_tags.findings[6] | 0.95 | the tagger's words |
| content_tags | Each unique record receives a CNP identifier plus names, cross-references, computed properties, descriptors, fingerprints, and chemical classifications. | content_tags.findings[7] | 0.95 | the tagger's words |
| content_tags | The database computes 73 fields for each unique natural product, while exposing a selected fraction in the web interface. | content_tags.findings[8] | 0.95 | the tagger's words |
| content_tags | A five-star score summarizes the completeness and trust of names, taxonomy, literature, and source provenance. | content_tags.findings[9] | 0.95 | the tagger's words |
| content_tags | All natural products receive at least one molecular name through source names, database lookup, or computed IUPAC naming. | content_tags.findings[10] | 0.95 | the tagger's words |
| content_tags | COCONUT provides a deglycosylated representation and computed NP-likeness scores alongside other molecular features. | content_tags.findings[11] | 0.95 | the tagger's words |
| content_tags | An extra provenance screen removed 24,880 SuperNatural II-only molecules that lacked positive natural-product evidence. | content_tags.findings[12] | 0.95 | the tagger's words |
| content_tags | Only 31.5 percent of records have organism taxonomy, 15.4 percent have continent-level geography, and 16.6 percent have a literature reference. | content_tags.findings[13] | 0.95 | the tagger's words |
| content_tags | Taxonomic attribution can be mistaken when symbionts or microbiomes rather than the sampled multicellular organism synthesize a compound. | content_tags.findings[14] | 0.95 | the tagger's words |
| content_tags | The database separates raw source records from unified curated records in two MongoDB collections. | content_tags.findings[15] | 0.95 | the tagger's words |
| content_tags | The implementation uses React and OpenChemLib at the front end and Kotlin, Java 11, Spring, and CDK at the back end. | content_tags.findings[16] | 0.95 | the tagger's words |
| content_tags | The web interface, back end, and database are Dockerized for local or cloud deployment. | content_tags.findings[17] | 0.95 | the tagger's words |
| content_tags | Simple search recognizes the input representation and routes it to indexed fields. | content_tags.findings[18] | 0.95 | the tagger's words |
| content_tags | Substructure search combines a PubChem-fingerprint bit screen with an exact CDK pattern matcher selected by the user. | content_tags.findings[19] | 0.95 | the tagger's words |
| content_tags | Similarity search uses MongoDB aggregation and an inverted index over PubChem fingerprint bits. | content_tags.findings[20] | 0.95 | the tagger's words |
| content_tags | The full dataset and project code are freely available without restriction. | content_tags.findings[21] | 0.95 | the tagger's words |
| content_tags | small molecules produced by living organisms also in: natural products | content_tags.definitions[0] | 0.95 | the tagger's words |
| content_tags | an aggregated open collection of elucidated and predicted natural products also in: COCONUT | content_tags.definitions[1] | 0.95 | the tagger's words |
| content_tags | a five-star scale of metadata completeness and source trust also in: annotation level | content_tags.definitions[4] | 0.95 | the tagger's words |
| content_tags | a molecular representation with sugar moieties removed for aglycon study | content_tags.definitions[6] | 0.95 | the tagger's words |
| content_tags | the MongoDB collection retaining original records from open sources also in: SourceNaturalProduct | content_tags.definitions[7] | 0.95 | the tagger's words |
| content_tags | the MongoDB collection of unified and curated natural products also in: UniqueNaturalProduct | content_tags.definitions[8] | 0.95 | the tagger's words |
| content_tags | a header search accepting names and common chemical identifiers or encodings also in: simple search | content_tags.definitions[9] | 0.95 | the tagger's words |
| content_tags | a fingerprint-prefiltered search confirmed by an exact graph-matching algorithm also in: substructure search | content_tags.definitions[10] | 0.95 | the tagger's words |
| content_tags | a programmatic query interface for workflow integration also in: REST API | content_tags.definitions[11] | 0.95 | the tagger's words |
| content_tags | over 120 — natural-product databases inventoried across the prior twenty years | content_tags.quantities[0] | 0.95 | the tagger's words |
| content_tags | 16% — inventoried natural-product databases no longer online | content_tags.quantities[1] | 0.95 | the tagger's words |
| content_tags | 40% — inventoried databases that are commercial | content_tags.quantities[2] | 0.95 | the tagger's words |
| content_tags | 53 — data sources contributing to COCONUT | content_tags.quantities[3] | 0.95 | the tagger's words |
| content_tags | 406076 — unique flat natural products in the October 2020 release | content_tags.quantities[4] | 0.95 | the tagger's words |
| content_tags | 730441 — records retaining stereochemistry when available | content_tags.quantities[5] | 0.95 | the tagger's words |
| content_tags | 5 to 210 — permitted heavy-atom range in structural quality control | content_tags.quantities[6] | 0.95 | the tagger's words |
| content_tags | 73 — computed fields in each unique-natural-product document | content_tags.quantities[7] | 0.95 | the tagger's words |
| content_tags | 5 stars — highest annotation quality | content_tags.quantities[8] | 0.95 | the tagger's words |
| content_tags | 1 star — lowest annotation quality | content_tags.quantities[9] | 0.95 | the tagger's words |
| content_tags | 24880 — SuperNatural II-only molecules removed by additional quality control | content_tags.quantities[10] | 0.95 | the tagger's words |
| content_tags | 31.5% — COCONUT records with at least one organism taxon | content_tags.quantities[11] | 0.95 | the tagger's words |
| content_tags | 134379 — natural products with at least one organism taxon | content_tags.quantities[12] | 0.95 | the tagger's words |
| content_tags | 15.4% — records with continent-level geographic provenance | content_tags.quantities[13] | 0.95 | the tagger's words |
| content_tags | 66068 — natural products with known continent-level geography | content_tags.quantities[14] | 0.95 | the tagger's words |
| content_tags | 16.6% — records with at least one literature reference | content_tags.quantities[15] | 0.95 | the tagger's words |
| content_tags | 70730 — natural products with at least one literature reference | content_tags.quantities[16] | 0.95 | the tagger's words |
| content_tags | 65% — taxonomically annotated natural products attributed only to plants | content_tags.quantities[17] | 0.95 | the tagger's words |
| content_tags | 0.5% — taxonomically annotated natural products attributed to animals | content_tags.quantities[18] | 0.95 | the tagger's words |
| content_tags | data provenance also in: data provenance | content_tags.variables[0] | 0.95 | the tagger's words |
| content_tags | stereochemistry also in: stereochemistry | content_tags.variables[1] | 0.95 | the tagger's words |
| content_tags | InChI keys without stereochemistry also in: InChI keys without stereochemistry | content_tags.variables[2] | 0.95 | the tagger's words |
| content_tags | annotation level also in: annotation level | content_tags.variables[3] | 0.95 | the tagger's words |
| content_tags | NP-likeness score also in: NP-likeness score | content_tags.variables[4] | 0.95 | the tagger's words |
| content_tags | producer taxonomy also in: producer taxonomy | content_tags.variables[5] | 0.95 | the tagger's words |
| content_tags | geographic location also in: geographic location | content_tags.variables[6] | 0.95 | the tagger's words |
| content_tags | PubChem fingerprints also in: PubChem fingerprints | content_tags.variables[7] | 0.95 | the tagger's words |
| content_tags | molecular descriptor values also in: molecular descriptor values | content_tags.variables[8] | 0.95 | the tagger's words |
Tags that could not be placed in the text:
What was deliberately not tagged, and why, is recorded per paper by the tagger. Where a paper has no such record, this page says so rather than implying that nothing was declined.