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Abstract
Food compounds and their molecular interactions are crucial for health and provide new chemotypes and targets for drug and nutraceutic design. Here we retrieve and analyze the complete set of published interactions of food compounds with human proteins, using the FooDB as compound set and ChEMBL as source of interactions. The data is analyzed in terms of 19 target classes and 19 compound classes, showing a small fraction of target assignment of the compounds (1.6%) and unraveling multiple gaps in the chemobiological space for these molecules. By using well established cheminformatic approaches (Similarity Ensemble Approach (SEA) combined with the maximum Tanimoto Coefficient to the nearest bioactive, “SEA + TC”) we achieve a much enhanced target assignment (64.2%), filling many of the gaps with target hypothesis for fast focused testing. By publishing these datasets and analyses we expect to provide a set of resources to speed up the full clarification of the chemobiological space of food compounds, opening new opportunities for drug and nutraceutic design.
Supplementary materials
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Figure S1
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Boxplot with distributions of drugEBIlity scores for both “food-specific” targets and “drug-specific” targets.
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Tables S1, S2, S4
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Table S1: FooDB compounds with published interactions, aggregated by inchikey. For each inchikey, the foodb_id, compound class, target, and target class are provided.
Table S2: FooDB compounds with predicted interactions, aggregated by inchikey. For each inchikey, the foodb_id, compound class, target, and target class are provided.
Table S4. Set of predicted interactions in SEA + TC (that uses ChEMBL25) experimentally validated in ChEMBL29.
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Table S3
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Full tldr predictions for all FooDB compounds. For each interaction, the compound identified, target name, affinity threshold, SEA p.value, TC, target description, SMILES, inchikey are provided.
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Table S5
Description
Set of most significant scaffolds for food compounds-target interactions. For each compound class, the most significant scaffold is shown for each target class, for compound class vs target class combinations with > 10 molecules and for scaffolds in > 2 molecules (see Methods).
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