Separation and identification of berberine in plant extracts using LC-MS for antibacterial activity against E. coli determination and artificial intelligence prediction for other activities

Abstract

Abstract A fast LC-MS method has been developed for the identification of berberine in plant extracts. The retention times for the standard berberine and berberine extracted from Berberis vulgaris, Berberis aquifolium, and Hydrastis canadensis were 1.80, 1.82, 1.79 and 1.79, respectively, using mobile phase of a mixture of ammonium acetate buffer and acetonitrile with gradient mode. The column used Waters Acquity BEH C18 (50 x 2.1 mm, 1.7 µm). The purity of the standard berberine was recorded as 98.86% with desired mass of 336 while these values were 61.82, 69.02 and 49.98% for berberine extracted from Berberis vulgaris, Berberis aquifolium and Hydrastis canadensis. In addition, an artificial intelligence technique was also applied to predict the possible activity of berberine against 27 known diseases. The results indicated berberine as the most active against Dengue larvicide, E. coli, Alzheimer and PTR L Major with 1.0 as the maximum probability. The outcomes reported herein are very important to determine the purity of the plants that extracted berberine in the future. The antibacterial activity of berberine was carried by MTT assay. The IC50 of berberine was calculated 136.3 µM against E. coli, while IC50 of a standard kanamycin taken as positive drug control calculated 10.87 µM. Also, the applied artificial intelligence may be extended to predict the biological activity of berberine or more diseases.