Antibiotic resistance genes(ARGs)are emerging environmental contaminants,with vertical gene transfer(VGT)in Escherichia coli(E.coli)contributing significantly to their spread.In this study,we sought to predict amino a...Antibiotic resistance genes(ARGs)are emerging environmental contaminants,with vertical gene transfer(VGT)in Escherichia coli(E.coli)contributing significantly to their spread.In this study,we sought to predict amino acid mutations in the DNA gyrase subunit A protein of E.coli,simulating resistance scenarios and evaluating the binding efficacy of quinolones(QNs),based on molecular docking analyses.To optimize QNs,we designed a three-dimensional quantitative structure-activity relationship model,thereby enabling the design of 153 substitutes.By screening for environmental friendliness and functional stability,we identified PM-55 and PM-58 as pharmacodynamically stable alternatives,using which the inhibition of VGT was enhanced by 65.52%and 75.86%,respectively.Furthermore,drug synergy experiments revealed that when combined with colistin sulfate E,this promoted the binding affinity of PM-58 to mutant proteins by 77.71%,mediated by an intensification of hydrophobic interactions and shorter hydrogen bonds.In addition,a machine learning-based random forest regression model was used to identify key molecular descriptors influencing drug synergy and the inhibition of ARGs,thereby providing a framework for designing sustainable antibiotic alternatives.This dual approach,which combines molecular modifications with drug synergy,offers practical solutions for mitigating the environmental dissemination of ARGs and will contribute to a more effective inhibition of antimicrobial resistance.展开更多
文摘Antibiotic resistance genes(ARGs)are emerging environmental contaminants,with vertical gene transfer(VGT)in Escherichia coli(E.coli)contributing significantly to their spread.In this study,we sought to predict amino acid mutations in the DNA gyrase subunit A protein of E.coli,simulating resistance scenarios and evaluating the binding efficacy of quinolones(QNs),based on molecular docking analyses.To optimize QNs,we designed a three-dimensional quantitative structure-activity relationship model,thereby enabling the design of 153 substitutes.By screening for environmental friendliness and functional stability,we identified PM-55 and PM-58 as pharmacodynamically stable alternatives,using which the inhibition of VGT was enhanced by 65.52%and 75.86%,respectively.Furthermore,drug synergy experiments revealed that when combined with colistin sulfate E,this promoted the binding affinity of PM-58 to mutant proteins by 77.71%,mediated by an intensification of hydrophobic interactions and shorter hydrogen bonds.In addition,a machine learning-based random forest regression model was used to identify key molecular descriptors influencing drug synergy and the inhibition of ARGs,thereby providing a framework for designing sustainable antibiotic alternatives.This dual approach,which combines molecular modifications with drug synergy,offers practical solutions for mitigating the environmental dissemination of ARGs and will contribute to a more effective inhibition of antimicrobial resistance.
