ChemTastesDB: A Curated Database of Molecular Tastants

<p><em><strong>ChemTastesDB</strong></em> is a database that includes curated information of 4075 molecular tastants. <strong><em>ChemTastesDB</em></strong> is distributed to the scientific community to expand the information of molecular tastants, which could assist the analysis of the relationships between molecular structure and taste, as well as <em>in</em> <em>silico</em> (QSAR/QSPR) studies for taste prediction. Examples of QSPR approaches for the prediction of molecular taste are given in the following publication: <em>Rojas, C., Abril-Gonz&aacute;lez, M., Ballabio, D. &amp; Garc&iacute;a, F. (2025). ChemTastesPredictor: An ensemble of machine learning classifiers to predict the taste of molecular tastants. Chemometrics and Intelligent Laboratory Systems. 261, 105380. <a href="https://doi.org/10.1016/j.chemolab.2025.105380">https://doi.org/10.1016/j.chemolab.2025.105380</a>.</em></p> <p>The 4075 molecular tastants are categorized into one of the five basic tastes (sweet, bitter, umami sour and salty), as well as to other classes related to non-basic tastes (tasteless, non-sweet, non-bitter, multitaste and miscellaneous). The molecules are categorized into following ten classes: sweet (1313), bitter (1615), umami (220), sour (49), salty (16), multitaste (179), tasteless (232), non-sweet (304), non-bitter (28), and miscellaneous (119).</p> <p><strong><em>ChemTastesDB</em></strong> provides the following information for each molecule: name, PubChem CID, CAS registry number, canonical SMILES string, class taste and the reference to the scientific sources from where data were retrieved. In addition, the molecular structure in the HyperChem (<em>.hin</em>) format of each compound is provided.</p> <p>This is version 2.1 of the <em><strong>ChemTastesDB</strong></em>. In this new version, 1131 newly curated compounds were added. These new molecules were retrieved from 52 new bibliographic references.</p>