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Synthesis, Molecular Docking, and 2D-QSAR Modeling of Quinoxaline Derivatives as Potent Anticancer Agents against Triple-negative Breast Cancer

机译:喹喔啉衍生物作为三阴性乳腺癌强效抗癌剂的合成、分子对接和二维QSAR建模

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Background: Breast carcinomas aka triple-negative breast cancers (TNBC) are one of the most complex and aggressive forms of cancers in females. Recently, studies have shown that these carcinomas are resistant to hormone-targeted therapies, which makes it a priority to search for effective and potential anticancer drugs. The present study aimed to synthesize and develop the 2D-quantitative structural activity relationship model (QSAR) of quinoxaline derivatives as a potential anticancer agent. Methods: Quinoxaline derivatives were designed and synthesized (8a-8i and 9a-9d) and the 2D-QSAR model against TNBC was developed using VLife MDS v4.4. The anticancer activity was investigated against the TNBC MDA-MB-231 cell line using an MTT cytotoxicity assay. Molecular docking studies along with the estimation of ADMET parameters were done using Discovery Studio. The most potent compound was docked against the beta-tubulin protein target (PDB: 4O2B), using the Autodock Vina v0.8 program. Results: Eleven derivatives of quinoxaline were designed and synthesized (8a-8i and 9a-9d) and a 2D-QSAR model was developed against the TNBC MDA-MB231 cell line. The regression coefficient values for the training set were (r(2)) 0.78 and (q(2)) 0.71. Further, external test set regression (pred_r(2)) was 0.68. Five molecular descriptors viz., energy dispersive (Epsilon3), protein-coding gene (T_T_C_6), molecular force field (MMFF_6), most hydrophobic hydrophilic distance (XA), and Z(comp) Dipole were identified. After ADMET, the best analog 8a showed the best activity against the TNBC cell line. The best-predicted hit '8a' was found to bind within the active site of the beta-tubulin protein target. Conclusion: The newly synthesized quinoxaline compounds could serve as potent leads for the development of novel anti-cancer agents against TNBC.
机译:背景:乳腺癌又名三阴性乳腺癌 (TNBC) 是女性最复杂和最具侵袭性的癌症形式之一。最近,研究表明,这些癌症对激素靶向治疗具有耐药性,这使得寻找有效和潜在的抗癌药物成为当务之急。本研究旨在合成和发展喹喔啉衍生物作为潜在抗癌剂的二维定量结构活性关系模型(QSAR)。方法:设计合成喹喔啉衍生物(8a-8i和9a-9d),利用VLife MDS v4.4建立抗TNBC的2D-QSAR模型。使用 MTT 细胞毒性测定法研究了针对 TNBC MDA-MB-231 细胞系的抗癌活性。使用Discovery Studio进行分子对接研究以及ADMET参数的估计。使用 Autodock Vina v0.8 程序将最有效的化合物对接到 β-微管蛋白靶标 (PDB: 4O2B)。结果:设计合成了喹喔啉的11种衍生物(8a-8i和9a-9d),并建立了针对TNBC MDA-MB231细胞系的2D-QSAR模型。训练集的回归系数值分别为(r(2))0.78和(q(2))0.71。此外,外部测试集回归(pred_r(2))为0.68。五个分子描述符,即。、能量色散(Epsilon3)、蛋白质编码基因(T_T_C_6)、分子力场(MMFF_6)、疏水距离(XA)和Z(comp)偶极子。ADMET后,最佳类似物8a对TNBC细胞系表现出最佳活性。发现最佳预测的命中“8a”在β-微管蛋白靶标的活性位点内结合。结论:新合成的喹喔啉类化合物可作为开发新型抗癌药物的有效线索。

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