Cancer is one of the leading causes of deaths globally. Despite many anticancer agents in the market, cancer stood as a major health concern to humanity due to the problems like drug resistance, toxicities and economic burden etc., and these issues strongly impose the scientists for the development of novel anticancer agents. Hence, in the current investigation, we performed the 2D-QSAR (Quantitative Structure-Activity Relationship) analysis of a series of compounds reported with a potential antiproliferative activity using multiple regression analysis and designed compounds from the obtained QSAR model. The generated Multiple Linear Regression (MLR) equations were validated both internally and externally. The applicability domain has been done for the developed model. Based on the generated QSAR equations, a series of 2-amino-5-substituted-1,3,4-thiadiazole derivatives were designed and their antiproliferative activity was predicted using the QSAR equations. Further, molecular docking studies were carried out for the designed compounds using Autodock 4 against Epidermal Growth Factor Receptor (EGFR) kinase. The compounds with good binding affinity were synthesized and characterized by FT-IR, NMR and mass spectroscopy and evaluated for their antiproliferative activity against MCF-7 and PC3 cell lines considering the overexpression of EGFR kinase in breast and prostate cancers. The generated best model exhibited an r² value of 0.93, q²_LOO = 0.92, r²_cv = 0.78. From the results, compound 3b and 3c exhibited good antiproliferative activity. The results of the study suggest that the synthesized active compound could serve as a lead for generating good biological agents against EGFR kinase.

癌症是全球死亡的主要原因之一。尽管市场上有许多抗癌药物，但由于耐药性、毒性和经济负担等问题，癌症已成为人类面临的主要健康问题，这些问题强烈要求科学家开发新型抗癌药物。因此，在目前的调查中，我们使用多元回归分析对一系列具有潜在抗增殖活性的化合物进行了 2D-QSAR（定量构效关系）分析，并从获得的 QSAR 模型中设计了化合物。生成的多元线性回归 (MLR) 方程经过内部和外部验证。已经为开发的模型完成了适用性域。基于生成的 QSAR 方程，一系列 2-amino-5-located-1,3，设计了 4-噻二唑衍生物，并使用 QSAR 方程预测了它们的抗增殖活性。此外，使用 Autodock 4 针对表皮生长因子受体 (EGFR) 激酶对设计的化合物进行了分子对接研究。合成了具有良好结合亲和力的化合物，并通过 FT-IR、NMR 和质谱进行了表征，并评估了它们对 MCF-7 和 PC3 细胞系的抗增殖活性，考虑到 EGFR 激酶在乳腺癌和前列腺癌中的过度表达。生成的最佳模型展示了一个 r 合成了具有良好结合亲和力的化合物，并通过 FT-IR、NMR 和质谱进行表征，并评估了它们对 MCF-7 和 PC3 细胞系的抗增殖活性，考虑到 EGFR 激酶在乳腺癌和前列腺癌中的过度表达。生成的最佳模型展示了一个 r 合成了具有良好结合亲和力的化合物，并通过 FT-IR、NMR 和质谱进行表征，并评估了它们对 MCF-7 和 PC3 细胞系的抗增殖活性，考虑到 EGFR 激酶在乳腺癌和前列腺癌中的过度表达。生成的最佳模型展示了一个 r²值为 0.93，q ² _LOO  = 0.92，r ² _cv  = 0.78。结果表明，化合物3b和3c表现出良好的抗增殖活性。研究结果表明，合成的活性化合物可以作为产生针对 EGFR 激酶的良好生物制剂的先导物。