Abstract
Red tides that occur off coasts have become a worldwide phenomenon over the past decades. In order to mitigate the damage of the red tides on the aquatic ecosystems, it is crucial to develop a method for predicting algicidal activities that requires less labor and time, and most importantly, this method can quickly screen potential algicides to control red tides. In this study, we have investigated the algicidal activity of 19 natural flavonoids against a typical red tide alga, Phaeocystis globosa. Our results indicate that after 5 days of flavonoid exposure, the half inhibition concentrations (IC50) ranged from 0.068 to 3.065 mg L−1, which showed the strong algicidal activities of the flavonoids. Furthermore, quantitative structure activity relationship (QSAR) model has been carried out between negative scale logarithm (pIC50) of the flavonoids and the corresponding molecular descriptors. The developed model was validated, both internally and externally, which displayed statistical robustness (R2 = 0.867, p = 0.0002, Q2LOO = 0.825, RMSEC = 0.182, Q2extF3 = 0.896, RMSEP = 0.161, CCC = 0.935). This indicates that the developed model was obtained successfully with satisfactory predictability and robustness for the future rapid screening of natural flavonoids with high inhibition activity on the red tide alga growth. Moreover, the main descriptors in the QSAR model were the molar refractivity, partition coefficient, lowest unoccupied molecular orbital, and highest occupied molecular orbital, illustrating that the molecular electro-chemical characteristics are significant in the algicidal actions of the flavonoids.
Red tides frequently occur worldwide and have become a global environment problem. Flavonoids showed great potential in allelopathic control of the excessive growth of red tide algae. In this study, the algicidal activity of 19 natural flavonoids was investigated on a typical red tide organism Phaeocystis globosa. Futhermore, we applied the quantitative structure-activity relationship (QSAR) model to the experimental data. The model between molecular descriptors of flavonoids and their antialgal activity displays statistical robustness, and 4 of 45 selected molecular descriptors were obtained by regression of training set. The numbers in the figure represent the half inhibition concentration (IC50) of flavonoids. Our results show that the algicidal activity of flavonoids is closely related to molar refraction, partition coefficient, lowest unoccupied molecular orbital, and highest occupied molecular orbital. The QSAR model can efficaciously predict the algicidal activity and provide insights into the inhibitory mechanisms of flavonoids.
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Acknowledgments
We thank Assoc. Prof. Mengmeng Tong from Zhejiang University for providing the red tide alga Phaeocystis globosa.
Funding
This study was financially supported by the National Natural Science Foundation of China (21677122 and 21876148), the open fund of the Key Laboratory of Integrated Marine Monitoring and Applied Technologies for Harmful Algal Blooms, SOA (MATHAB201809), the National Key R and D Program of China (2016YFC1402104), the Major Science and Technology Program for Water Pollution Control and Treatment (2018ZX07208-009), the open fund of the Laboratory of Marine Ecosystem, Biogeochemistry, Second Institute of Oceanography, SOA (LMEB201709), and the China Scholarship Council (201806325035).
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Highlights
1. We first investigated the algicidal activity of 19 natural flavonoids to the typical red tide algae, Phaeocystis globsa, which shows strong algicidal activities of the flavonoids;
2. We introduce the quantitative structure-activity relationship (QSAR) model to predict the algicidal activity of flavonoids;
3. The QSAR model can efficaciously predict the algicidal activity of test compounds and provide insights into the inhibitory mechanisms of flavonoids.
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Xiao, X., Li, C., Huang, H. et al. Inhibition effect of natural flavonoids on red tide alga Phaeocystis globosa and its quantitative structure-activity relationship. Environ Sci Pollut Res 26, 23763–23776 (2019). https://doi.org/10.1007/s11356-019-05482-7
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DOI: https://doi.org/10.1007/s11356-019-05482-7