2024/05/23 by Lamkadmi, Hanae, Taoufik, Hamid, Lahrache, Ayoub +3
paper · doi:10.48419/imist.prsm/rhazes-v19.48694
Lignans are crucial chemical compounds recognized for their potential in drug discovery. Indeed, many lignans have shown antiproliferative and anticancer effects both in vitro and in Vivo on the broad category of cancers [1]. In this study, twenty-five molecules derived from lignans [2] were used to design powerful anti-cancer drugs using the 2D-QSAR method to generate the model linking chemical structures and the best-selected numerical descriptors [3]. Molecule structures were drawn using Marvin Sketch software and, then, were optimized by the molecular force field (MM2) method included in Chembiooffice. A set of molecular descriptors were calculated using molecular operating environment (MOE) software [4]. The Partial Least Squares (PLS) were used to select the four best descriptors (b1rotN, SlogPVSA9, PEOEVSA+3, vsurfID8) for the 2D-QSAR model. The best 2D-QSAR model induced by the method (PLS) shows a high correlation with the best statistical metrics [5], such as R2=0.92, RMSE=0.18, Q2=0.88, R2pred=0.60. The statistical results show that the established 2D-QSAR model is highly significant at level α=0.05. Moreover, the Student test suggests that the selected descriptors are more relevant and very significant at the level α = 0.05. The selected descriptors indicate that the optimization of the balance hydrophobic and solubility of this series of compounds would predict the structural requirements of the studied compounds to improve their anticancer activity [4]. According to the established 2D-QSAR model, it is achievable to design new compounds that exhibit strong potential as anti-cancer agents.