Insight into structural requirements of antiamoebic flavonoids: 3D‐QSAR and G‐QSAR studies. (26th June 2018)

• Record Type: Journal Article
• Authors: Fatima, Shehnaz; Gupta, Payal; Agarwal, Subhash Mohan
• Is Part Of: Chemical biology & drug design. Volume 92:Number 4(2018)
• Page Start: 1743
• Page End: 1749
• Publication Date: 2018-06-26
• Subjects: amoebiasis -- antiamoebic -- Entamoeba histolytica -- flavonoids -- G‐QSAR -- QSAR; Drugs -- Design -- Periodicals; Pharmaceutical chemistry -- Periodicals; Biochemistry -- Periodicals; 615.19005
• DOI: 10.1111/cbdd.13343
• Languages: English
• ISSNs: 1747-0277

Abstract

Abstract : Plant‐based flavonoids have been found to exhibit strong inhibitory capability against Entamoeba histolytica . So, various QSAR models have been developed to identify the critical features that are responsible for the potency of these molecules. 3D‐QSAR analysis using k ‐nearest neighbour molecular field analysis via stepwise forward–backward variable selection method showed best results for both internal and external predictive ability of the model (i.e., q 2 = 0.64 and pred_ r 2 = 0.56). Also, a group‐based QSAR (G‐QSAR) model was developed based on partial least squares regression combined with stepwise forward–backward variable selection method. It gave best parametric results ( r 2 = 0.74, q 2 = 0.56 and pred_ r 2 = 0.54) which implied that the model is highly predictive. 3D‐QSAR established that presence/absence of bulk near rings B and C is important in deciding the inhibitory potential of these molecules. Additionally, G‐QSAR provided site‐specific clue wherein modifications related to molecular weight, electronegativity and separation of an oxygen atom in rings A and C can result in enhanced biological activity. To the best of the author's knowledge, this is the first QSAR study of antiamoebic flavonoids, and therefore, we expect the results to be useful in the design of more potent antiamoebic inhibitors. Abstract : Plant‐based flavonoids have strong antiamoebic activity; therefore, we generated 3D‐ and G‐QSAR models to identify the features responsible for their bioactivity. The generated 3D‐ and G‐QSAR model indicated descriptors related to electronegativity, molecular weight and distance of oxygen atom play an important role in deciding the activity of the molecules. We have discussed contributions of each of these molecular descriptors and expect that the study would provide insight for designing better antiamoebic inhibitors.