Studies On Antibacterial Quantitative Structure-Activity Relationship Against Escherichia Coli Of Flavoniods Based On Memberane Interaction

Flavonoids are widely present in the plant kingdom exhibiting a broad range of physiological and pharmacological activities.It is the rich resource and the great antibacterial activity that makes flavonoids one of the best choices for the natural preservative. In this study, we choose Escherichia coli as the target of flavonoids and analyze the relationship between their structure and antibacterial activity. To determine the relationship between the antibacterial activity and the membrane interaction, liposomes were used as structural models of biological membranes. The antibacterial predicting capacities and the mechanism involved in the antimicrobial action of the tested flavonoids were further evaluated through2D,3D-QSAR method.The main results are listed as follows:1. The inhibitory effects of flavonoids on Escherichia coli were evaluated by using microbroth dilution assay, represented by MIC50. The relative antibacterial activities were determined as: kaempferol﹥quercetin﹥chrysin﹥luteolin﹥baicalein﹥tangeritin﹥5,6,7,4’-tetramethoxyflavone and daidzein﹥genistin﹥ononin﹥puerarin.Based on the MIC50values, primary assessment of the relationship between flavonoids’ structure and their antibacterial activity has been done.8-OCH3and3-OH enhance inhibition of flavonoids while4or5additional OCH3groups in the A ring and B ring and glycosidic group on C-7and C-8reduce the inhibition.2. Liposomes made of DPPC/DPPG (v/v=1/2) were used to simulate the membrane of E.coli. The interaction of flavonoids with the model membrane was assessed by DPH fluorescence polarization measurements, indicating that membrane interaction could be an important mechanism of the antibacterial activities of flavonoids.5flavonoids rigidified the model membrane; whereas the polymethoxyflavones and isoflavonoids increased membrane fluidity. There is a significant positive correlation between antibacterial capacity and membrane rigidification effect. 3. MIC50values of11flavonoids were used as the biological activity data set and quantum chemical descriptors were calculated by DFT, and the2D-QSAR model of flavonoids was built by using linear regression analysis. The model is pMIC50=2.749+0.391CLogP+1.946C3. q2=0.769, R2pred=0.691, indicating the QSAR model is strong and predictive, and can be used to explain the antibacterial mechanism of flavonoids. The model demonstrated that hydrophobicity and electronic property are key factors in the antibacterial activity of flavonoids and hydrophobicity plays a major role. Higher values for CLogP and high positive charges on C3lead to an increase in antibacterial activity.4. MIC50values of11flavonoids were used as the biological activity data set, the CoMFA and CoMSIA model of flavonoids were built by using sybyl7.3. q2=0.523/0.613, r2=0.998/0.999. The results of contour maps suggested that electron-accepting groups on the A ring C-5, C-8, B ring C-4’ and C-5’, electron-donating groups on B ring C-3’, C-6’and C ring C-3; bulky groups on A ring C-5, C ring C-3and the B ring, small groups on A ring C-6, C-7, C-8and B ring C-2’; hydrophobic groups on A ring C-7and C-8, hydrophilic groups on C ring C-3could enhance the antibacterial activity of flavonoids.