Lorca Marcos, Muscia Gisela C, Pérez-Benavente Susana, Bautista José M, Acosta Alison, González Cesar, Sabadini Gianfranco, Mella Jaime, Asís Silvia E, Mellado Marco
Instituto de Química y Bioquímica, Facultad de Ciencias, Universidad de Valparaíso, Av. Gran Bretaña 1111, Valparaíso 2360102, Chile.
Departamento de Ciencias Químicas, Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires, Junín 956, C1113AAB Ciudad Autónoma de Buenos Aires, Buenos Aires 1113, Argentina.
Pharmaceuticals (Basel). 2024 Jul 4;17(7):889. doi: 10.3390/ph17070889.
Malaria is an infectious disease caused by spp. parasites, with widespread drug resistance to most antimalarial drugs. We report the development of two 3D-QSAR models based on comparative molecular field analysis (CoMFA), comparative molecular similarity index analysis (CoMSIA), and a 2D-QSAR model, using a database of 349 compounds with activity against the 3D7 strain. The models were validated internally and externally, complying with all metrics (q > 0.5, r > 0.6, r > 0.5, etc.). The final models have shown the following statistical values: r CoMFA = 0.878, r CoMSIA = 0.876, and r 2D-QSAR = 0.845. The models were experimentally tested through the synthesis and biological evaluation of ten quinoline derivatives against 3D7. The CoMSIA and 2D-QSAR models outperformed CoMFA in terms of better predictive capacity (MAE = 0.7006, 0.4849, and 1.2803, respectively). The physicochemical and pharmacokinetic properties of three selected quinoline derivatives were similar to chloroquine. Finally, the compounds showed low cytotoxicity (IC > 100 µM) on human HepG2 cells. These results suggest that the QSAR models accurately predict the toxicological profile, correlating well with experimental in vivo data.
疟疾是一种由疟原虫属寄生虫引起的传染病,对大多数抗疟药物具有广泛的耐药性。我们报告了基于比较分子场分析(CoMFA)、比较分子相似性指数分析(CoMSIA)开发的两个3D-QSAR模型以及一个2D-QSAR模型,使用了一个包含349种对3D7菌株有活性的化合物的数据库。这些模型在内部和外部进行了验证,符合所有指标(q>0.5,r>0.6,r>0.5等)。最终模型显示出以下统计值:r CoMFA = 0.878,r CoMSIA = 0.876,r 2D-QSAR = 0.845。通过对十种喹啉衍生物针对3D7进行合成和生物学评估对模型进行了实验测试。在预测能力方面,CoMSIA和2D-QSAR模型优于CoMFA(平均绝对误差分别为0.7006、0.4849和1.2803)。三种选定喹啉衍生物的物理化学和药代动力学性质与氯喹相似。最后,这些化合物对人HepG2细胞显示出低细胞毒性(IC>100µM)。这些结果表明,QSAR模型准确预测了毒理学概况,与体内实验数据相关性良好。