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• W2891411062 abstract "Infectious diseases are a health problem today and have high mortality rates with a wide diversity of potentially pathogenic microorganisms. Research that is based either on the search for new drugs from plants or on the improvement of phytotherapeutics is prominent and continues to play an important role nowadays. From this perspective, use of in silico studies to carry out investigations of new molecules potentially active for methicillin-resistant Staphylococcus aureus and Escherichia coli using an in-house database with 421 different secondary metabolites selected from the literature from Solanum genus was performed. We also realized an in vitro study with strains of S. aureus and E. coli and compared the results. Two databases from ChEMBL were selected, the first one with activity against methicillin-resistant S. aureus and another against E. coli. The compounds were classified according to the pIC50 values to generate and validate the model using a “Random Forest”. The “Random Forest” prediction model for methicillin-resistant S. aureus obtained an accuracy of 81%, area under the Receiver Operating Characteristic curve of 0.885, selecting eight molecules with an active potential above 60%. The prediction model for E. coli obtained an accuracy rate of 88%, area under the Receiver Operating Characteristic curve of 0.932, selecting four molecules with potential probability above 84%. Rutin proved to be potentially active in the in silico study for S. aureus and E. coli. Microbiological tests have shown that rutin has activity only for E. coli. An interaction study with strains of S. aureus ATCC 25923, a standard strain sensitive to all antibiotics, and SAM-01, a multidrug-resistant strain, was designed. There was interaction only between rutin and oxacillin, one of the three antibiotics studied in the interaction, for the strain SAM-01, reducing the resistance of this strain." @default.
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• W2891411062 date "2018-11-01" @default.
• W2891411062 modified "2023-09-25" @default.
• W2891411062 title "Virtual screening of secondary metabolites of the genus Solanum with potential antimicrobial activity" @default.
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• W2891411062 doi "https://doi.org/10.1016/j.bjp.2018.08.003" @default.
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