Structure-Activity Relationship of Cinnamaldehyde Analogs as Inhibitors of AI-2 Based Quorum Sensing and Their Effect on Virulence of Vibrio spp

Background: Many bacteria, including Vibrio spp., regulate virulence gene expression in a cell-density dependent way through a communication process termed quorum sensing (QS). Hence, interfering with QS could be a valuable novel antipathogenic strategy. Cinnamaldehyde has previously been shown to inhibit QS-regulated virulence by decreasing the DNA-binding ability of the QS response regulator LuxR. However, little is known about the structure-activity relationship of cinnamaldehyde analogs. Methodology/Principal Findings: By evaluating the QS inhibitory activity of a series of cinnamaldehyde analogs, structural elements critical for autoinducer-2 QS inhibition were identified. These include an alpha, beta unsaturated acyl group capable of reacting as Michael acceptor connected to a hydrophobic moiety and a partially negative charge. The most active cinnamaldehyde analogs were found to affect the starvation response, biofilm formation, pigment production and protease production in Vibrio spp in vitro, while exhibiting low cytotoxicity. In addition, these compounds significantly increased the survival of the nematode Caenorhabditis elegans infected with Vibrio anguillarum, Vibrio harveyi and Vibrio vulnificus. Conclusions/Significance: Several new and more active cinnamaldehyde analogs were discovered and they were shown to affect Vibrio spp. virulence factor production in vitro and in vivo. Although ligands for LuxR have not been identified so far, the nature of different cinnamaldehyde analogs and their effect on the DNA binding ability of LuxR suggest that these compounds act as LuxR-ligands

QSAR studies on a number of pyrrolidin-2-one antiarrhythmic arylpiperazinyls

The activity of a number of 1-[3-(4-arylpiperazin-1-yl)propyl]pyrrolidin-2-one antiarrhythmic (AA) agents was described using the quantitative structure–activity relationship model by applying it to 33 compounds. The molecular descriptors of the AA activity were obtained by quantum chemical calculations combined with molecular modeling calculations. The resulting model explains up to 91% of the variance and it was successfully validated by four tests (LOO, LMO, external test, and Y-scrambling test). Statistical analysis shows that the AA activity of the studied compounds depends mainly on the PCR and JGI4 descriptors