Pathogen infections, exacerbated by emerging drug resistance, remain among the most challenging health issues, for which multitargeting approaches may offer effective solutions. In this context, medicinal plants, including essential oils, provide complex mixtures of diverse molecules that can exert therapeutic effects, either alone or synergistically with established antibiotics. Although several databases comprehensively collect information on the antibacterial properties of medicinal plants, including chemical composition, bioactivity data, and ethnobotanical uses, there is a notable lack of tools to hypothesize mechanisms of action. To address this gap, we developed a computational pipeline that integrates chemoinformatics and bioinformatics, specifically designed for scenarios in which only the chemical composition of a complex mixture of natural phytocompounds is available. Beginning with an ultralarge, structure-based screening across thousands of proteins and their potential binding sites of six bacterial species, we used the predicted targets as input for bioinformatics tools commonly employed in the omics fields, such as pathway enrichment analysis and network analysis. Using this pipeline, we modeled how the essential oils of thyme, oregano, and cinnamon exert antibacterial activity against six bacterial pathogens. Applied here in the context of urinary tract infection, but extendable to other therapeutic scenarios, this pipeline provides a novel protocol for mode of action investigation and experimental prioritization, to be applied in drug discovery involving natural substances.
Thyme, Oregano, and Cinnamon Essential Oils: Investigating Their Molecular Mechanism of Action for the Treatment of Bacteria-Induced Cystitis
Carosati, Emanuele
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2026-01-01
Abstract
Pathogen infections, exacerbated by emerging drug resistance, remain among the most challenging health issues, for which multitargeting approaches may offer effective solutions. In this context, medicinal plants, including essential oils, provide complex mixtures of diverse molecules that can exert therapeutic effects, either alone or synergistically with established antibiotics. Although several databases comprehensively collect information on the antibacterial properties of medicinal plants, including chemical composition, bioactivity data, and ethnobotanical uses, there is a notable lack of tools to hypothesize mechanisms of action. To address this gap, we developed a computational pipeline that integrates chemoinformatics and bioinformatics, specifically designed for scenarios in which only the chemical composition of a complex mixture of natural phytocompounds is available. Beginning with an ultralarge, structure-based screening across thousands of proteins and their potential binding sites of six bacterial species, we used the predicted targets as input for bioinformatics tools commonly employed in the omics fields, such as pathway enrichment analysis and network analysis. Using this pipeline, we modeled how the essential oils of thyme, oregano, and cinnamon exert antibacterial activity against six bacterial pathogens. Applied here in the context of urinary tract infection, but extendable to other therapeutic scenarios, this pipeline provides a novel protocol for mode of action investigation and experimental prioritization, to be applied in drug discovery involving natural substances.Pubblicazioni consigliate
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