Use of 1,2,3-triazole Derivatives as Potential Inhibitors Blood Cancer, 3D-QSAR, Molecular Docking, and In-silico Pharmacokinetic and Toxicological Studies
Letters in Applied NanoBioScience · 2024
Recently, several types of cancer have been rising, and among these types of cancer, blood cancer has become a global problem, hence the discovery of new anticancer agents by computational chemistry. To improve and propose new compounds with anticancer activity, a quantitative three-dimensional structure-activity study (3D-QSAR) on anticancer analogs A 3D QSAR model based on Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) was created. Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) were established. Good stability of the model was obtained using the CoMFA model (Q2= 0.60; R2=0.97; R=0.75) and the best model CoMSIA (Q2=0.61; R2=0.92; R=0.86). The predictive capacity of the developed model was evaluated by external validation using the statistical indices of A. Tropshak. Roy, A. Golbraikh, and an internal validation by the Y-randomization test. The Docking results showing the interest of amino acids Gly31; Cys41 for anticancer activity and the steric and electrostatic field contours of CoMFA model were monitored. Based on this result, 24 molecules with anticancer activity were proposed. Moreover, ADMET outcomes show that this could help develop new cancer drugs.