Nutrition is a fundamental aspect in human life development, both from a socio-economic and medical perspective. In recent years, new personalized approaches have been added to the biochemical study of nutrients. These approaches consider both the effect of foods on the body and the role of genes in metabolizing or digesting different nutrients. Although drug-food interactions have been known for decades, there is a lack of studies that address these processes in a comprehensive way, using structural and computational biochemistry techniques. In this paper we develop a method to predict potential interactions between foods and drugs based on the structural similarity between food compounds and medications. Our results have produced a database and an app to consult potential interactions between drugs and foods that we have called FARFOOD. Additionally, we validated two of these potential interactions with widely used drugs (lisinopril and bupropion) through structural docking between the ligand protein and the food compounds that are structurally similar to the drug. Moreover, patient surveys are used in the lisinopril and bupropion cases in addition to allopurinol to assess the possible effects of the potentially interacting foods on the symptoms of the conditions for which the medication is prescribed. In summary, this manuscript presents an interesting computational resource for predictive food-drug interaction analysis.

The authors have declared no competing interest.

This paper was funded by the Spanish Ministry of Science through the projects TED2021-130036B-I00 and PID2020-117467RB-I00 (to SMN and ACR), and PID2021-126905NB-I00 and TED2021-130560B-I00 (to JMCG).

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The study protocol was reviewed by the Ethics Board of the University of Extremadura, and approved with the reference number 167/2023.

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