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ChemTastesDB: A curated database of molecular tastants
The purpose of this work is the creation of a chemical database named ChemTastesDB that includes both organic and inorganic tastants. The creation, curation pipeline and the main features of the database are described in detail. The database includes 2944 verified and curated compounds divided into...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8991844/ https://www.ncbi.nlm.nih.gov/pubmed/35415670 http://dx.doi.org/10.1016/j.fochms.2022.100090 |
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author | Rojas, Cristian Ballabio, Davide Pacheco Sarmiento, Karen Pacheco Jaramillo, Elisa Mendoza, Mateo García, Fernando |
author_facet | Rojas, Cristian Ballabio, Davide Pacheco Sarmiento, Karen Pacheco Jaramillo, Elisa Mendoza, Mateo García, Fernando |
author_sort | Rojas, Cristian |
collection | PubMed |
description | The purpose of this work is the creation of a chemical database named ChemTastesDB that includes both organic and inorganic tastants. The creation, curation pipeline and the main features of the database are described in detail. The database includes 2944 verified and curated compounds divided into nine classes, which comprise the five basic tastes (sweet, bitter, umami sour and salty) along with four additional categories: tasteless, non-sweet, multitaste and miscellaneous. ChemTastesDB provides the following information for each tastant: name, PubChem CID, CAS registry number, canonical SMILES, class taste and references to the scientific sources from which data were retrieved. The molecular structure in the HyperChem (.hin) format of each chemical is also made available. In addition, molecular fingerprints were used for characterizing and analyzing the chemical space of tastants by means of unsupervised machine learning. ChemTastesDB constitutes a useful tool to the scientific community to expand the information of taste molecules and to assist in silico studies for the taste prediction of unevaluated and as yet unsynthetized compounds, as well as the analysis of the relationships between molecular structure and taste. The database is freely accessible at https://doi.org/10.5281/zenodo.5747393. |
format | Online Article Text |
id | pubmed-8991844 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-89918442022-04-11 ChemTastesDB: A curated database of molecular tastants Rojas, Cristian Ballabio, Davide Pacheco Sarmiento, Karen Pacheco Jaramillo, Elisa Mendoza, Mateo García, Fernando Food Chem (Oxf) Research Article The purpose of this work is the creation of a chemical database named ChemTastesDB that includes both organic and inorganic tastants. The creation, curation pipeline and the main features of the database are described in detail. The database includes 2944 verified and curated compounds divided into nine classes, which comprise the five basic tastes (sweet, bitter, umami sour and salty) along with four additional categories: tasteless, non-sweet, multitaste and miscellaneous. ChemTastesDB provides the following information for each tastant: name, PubChem CID, CAS registry number, canonical SMILES, class taste and references to the scientific sources from which data were retrieved. The molecular structure in the HyperChem (.hin) format of each chemical is also made available. In addition, molecular fingerprints were used for characterizing and analyzing the chemical space of tastants by means of unsupervised machine learning. ChemTastesDB constitutes a useful tool to the scientific community to expand the information of taste molecules and to assist in silico studies for the taste prediction of unevaluated and as yet unsynthetized compounds, as well as the analysis of the relationships between molecular structure and taste. The database is freely accessible at https://doi.org/10.5281/zenodo.5747393. Elsevier 2022-02-21 /pmc/articles/PMC8991844/ /pubmed/35415670 http://dx.doi.org/10.1016/j.fochms.2022.100090 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Rojas, Cristian Ballabio, Davide Pacheco Sarmiento, Karen Pacheco Jaramillo, Elisa Mendoza, Mateo García, Fernando ChemTastesDB: A curated database of molecular tastants |
title | ChemTastesDB: A curated database of molecular tastants |
title_full | ChemTastesDB: A curated database of molecular tastants |
title_fullStr | ChemTastesDB: A curated database of molecular tastants |
title_full_unstemmed | ChemTastesDB: A curated database of molecular tastants |
title_short | ChemTastesDB: A curated database of molecular tastants |
title_sort | chemtastesdb: a curated database of molecular tastants |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8991844/ https://www.ncbi.nlm.nih.gov/pubmed/35415670 http://dx.doi.org/10.1016/j.fochms.2022.100090 |
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