Discovery of novel anti-cyanobacterial allelochemicals by multi-conformational QSAR approach

Abstract

Microcystis aeruginosa causes cyanobacterial harmful algal blooms (cHABs) in various freshwater environments. Due to global climate change, the cHABs have even spread to estuaries and coasts. Plant-derived flavones have been reported as allelochemicals that efficiently inhibit the growth of M. aeruginosa. Quantitative structure-activity relationship (QSAR) was applied to investigate the factors affecting the M. aeruginosa inhibitory activity of flavones, and to discover novel allelochemicals against M. aeruginosa. We constructed 2D and 3D-QSAR models based on the half maximum inhibitory concentration (IC50) of 22 flavones against M. aeruginosa, using molecular descriptors from multiple stable conformations. Both models showed satisfactory performances (2D-QSAR: r2=0.899, q2=0.596, rtest2=0.801; 3D-QSAR: r2=0.810, q2=0.516, rtest2=0.897). The 2D-QSAR model indicates that the anti-cyanobacterial activity is positively correlated with minimum and maximum surface electrostatic potential, and negatively correlated with polarity index and polar surface area. Through the 3D-QSAR approach, electronegative hydroxyl groups in 5- and 4′-position were favorable for the anti-cyanobacterial activity. In addition, we selected six untested flavones that fit the “activity-favorable” pattern of the visualized 3D-QSAR model. Five of the external flavones exhibited significant cyanobacterial inhibitory ability at their predicted IC50 by the 3D-QSAR model. In particular, diosmetin achieved an inhibition rate of 70.50±4.74%, which was much higher than expected. The flavones screened by the 3D-QSAR model are novel cyanobacterial inhibitors and should be fully exploited to mitigate cHABs.