QSAR Analysis and ADMET Prediction of Tamoxifen Derivatives Using LFER Hansch Model - Andzar Fikranus Shofa; Rawwdha Luthfi Nur Muhammad; Norma Adityaningsih Prameswari; Sendi Handika Putra; Aisyah Afifah Setiawan; Dhia Salsabila Rizki (Pharmacy Department, Faculty of Health Sciences, UIN Syarif Hidayatullah Jakarta, Indonesia, 2025)
Tamoxifen is a pharmaceutical compound that can be widely used in the therapeutic regimen for breast cancer, particularly for postmenopausal women. Nevertheless, this clinical efficacy is frequently diminished and limited due to the emergence of drug resistance and heterogeneous therapeutic impacts with different degrees of severity. This has led to the discovery of structurally connected compounds that are more effective than tamoxifen. The current research study describes QSAR modeling and predicting the ADMET parameters of tamoxifen derivatives for the treatment of breast cancer. SPSS software was used for analysis of multiple linear regression and found the pIC50 = -0.059CLogP + 0.759LUMO - 0.011MR + 3.444. Model validation yielded R = 0.921, R² = 0.848 and Q² = 0.651, which suggests high predictability. The most important characteristic being LUMO energy, the second most important descriptor was followed by CLogP and MR. The ADMET prediction showed high intestinal absorption values (HIA > 90%) and satisfactory permeability over skin. Water solubility was impaired but also low. The metabolism of compounds seemed to predominantly occur via CYP3A4 enzyme. However, LD50 values were of acceptable size, ranging from 324 to 3000 mg/kg (within the safety profile). The findings of this work will thus show help in designing anticancer tamoxifen derivative products with the least toxicity. Additional structural optimization is advocated to achieve maximal therapeutic benefit and least toxicity.