3D-QSAR Study of the Chalcone Derivatives as Anticancer Agents

Abstract

For their biological properties and particularly for their anticancer activities, chalcones are widely studied. In this work, we have submitted diverse sets of chalcone derivatives to the 3D-QSAR (3-dimensional quantitative structural-activity relationship) to study their anticancer activities against HTC116 (human colon cancer), relying on the 3-dimensional descriptors: steric and electrostatic descriptors for the CoMFA (comparative molecular field analysis) method and steric, electrostatic, hydrophobic, H-bond donor, and H-bond acceptor descriptors for the CoMSIA method. CoMFA as well as the CoMSIA model have encouraging values of the cross-validation coefficient (Q2) of 0.608 and 0.806 and conventional correlation coefficient (R2) of 0.960 and 0.934, respectively. Furthermore, values of R2test have been obtained as 0.75 and 0.90, respectively. Besides, y-randomization test was also performed to validate our 3D-QSAR models. Based on these satisfactory results, ten new compounds have been designed and predicted by in silico ADMET method. This study could expand the understanding of chalcone derivatives as anticancer agents and would be of great help in lead optimization for early drug discovery of highly potent anticancer activity.

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“…The contour map interpretation of the CoMFA and CoMSIA models generated is one of the most attractive aspects of the 3D-QSAR analysis which involves the visualization of all favoured and disfavoured regions of the molecular fields surrounding the molecules as bioactivities functions ( ElMchichi et al., 2020 ). Molecule 11 with the highest activity was chosen as a template to examine the most prominent field contributions for the studied dataset.…”

Integration of Ligand-Based and Structure-Based Methods for the Design of Small-Molecule TLR7 Antagonists

“…Data on 54 TLR7 antagonist compounds, along with their biological activities, were collected from the previous literature [29,32,33,35,41]. Experimental activity (IC 50 ) was uniformly maintained to the micromolar unit (µM) and converted to the logarithmic unit (pIC 50 ) [70]. The molecules were subsequently aligned, energy-minimized through a consistent forcefield (CFF), and subjected to compute the 2D molecular descriptors using the AlvaDesc v2.0.4 tool via an online chemical database v4.2.131 (https://ochem.eu, accessed on 7 February 2022) [42] to eliminate the complexity of various 3D conformational spaces.…”

“…The lowest energy conformation (minimized through CFF) of the most active compound (32, IC 50 : 0.43 µM) is usually used as a reference. The dataset was aligned using the common core of the active molecule as a reference template by using a field fit method based on the combination of steric and electrostatic fields available in Discovery Studio v18.1 client [70]. The alignment had a major impact on the prediction accuracy and statistical efficiency of the 3D-QSAR models.…”

Molecular Modeling Studies of C-Glycosylfavone Derivatives as GSK-3β Inhibitors Based on QSAR and Docking Analysis

“…Partial-least-squares (PLS) regression is a linear regression method [20,21], especially useful in the cases where the number of descriptors is greater than the number of observations (dataset compounds), and in the cases where the dataset compounds contain highly inter-correlated descriptors. Here, the PLS method was applied to generate the linear 2D-QSAR model, using the values of pIC50 as dependent variables (Y variables) and the significant selected descriptors as independent variables (X variables).…”