Computational Intelligence and Bioinformatics Laboratory, Department of Computer Science, Jamia Millia Islamia, New Delhi, 110025, India.
Mol Divers. 2024 Jun;28(3):1189-1202. doi: 10.1007/s11030-023-10648-0. Epub 2023 Apr 14.
Lung cancer is the second most common cancer, which is the leading cause of cancer death worldwide. The FDA has approved almost 100 drugs against lung cancer, but it is still not curable as most drugs target a single protein and block a single pathway. In this study, we screened the Drug Bank library against three major proteins- ribosomal protein S6 kinase alpha-6 (6G77), cyclic-dependent protein kinase 2 (1AQ1), and insulin-like growth factor 1 (1K3A) of lung cancer and identified the compound 5-nitroindazole (DB04534) as a multitargeted inhibitor that potentially can treat lung cancer. For the screening, we deployed multisampling algorithms such as HTVS, SP and XP, followed by the MM\GBSA calculation, and the study was extended to molecular fingerprinting analysis, pharmacokinetics prediction, and Molecular Dynamics simulation to understand the complex's stability. The docking scores against the proteins 6G77, 1AQ1, and 1K3A were - 6.884 kcal/mol, - 7.515 kcal/mol, and - 6.754 kcal/mol, respectively. Also, the compound has shown all the values satisfying the ADMET criteria, and the fingerprint analysis has shown wide similarities and the water WaterMap analysis that helped justify the compound's suitability. The molecular dynamics of each complex have shown a cumulative deviation of less than 2 Å, which is considered best for the biomolecules, especially for the protein-ligand complexes. The best feature of the identified drug candidate is that it targets multiple proteins that control cell division and growth hormone mediates simultaneously, reducing the burden of the pharmaceutical industry by reducing the resistance chance.
肺癌是第二大常见癌症,也是全球癌症死亡的主要原因。美国食品和药物管理局 (FDA) 已批准近 100 种治疗肺癌的药物,但由于大多数药物针对单一蛋白质并阻断单一途径,因此仍然无法治愈。在这项研究中,我们筛选了 Drug Bank 文库中的三种主要蛋白质-核糖体蛋白 S6 激酶 alpha-6 (6G77)、细胞周期蛋白依赖性激酶 2 (1AQ1) 和胰岛素样生长因子 1 (1K3A),并确定了化合物 5-硝基吲唑 (DB04534) 作为一种多靶点抑制剂,可能治疗肺癌。为了进行筛选,我们部署了 HTVS、SP 和 XP 等多采样算法,然后进行 MM\GBSA 计算,并将研究扩展到分子指纹分析、药代动力学预测和分子动力学模拟,以了解复合物的稳定性。与蛋白质 6G77、1AQ1 和 1K3A 的对接得分分别为-6.884 kcal/mol、-7.515 kcal/mol 和-6.754 kcal/mol。此外,该化合物还表现出所有符合 ADMET 标准的值,指纹分析显示出广泛的相似性,WaterMap 分析表明该化合物具有适用性。每个复合物的分子动力学都显示累积偏差小于 2Å,这被认为是生物分子的最佳选择,尤其是对于蛋白质-配体复合物。鉴定出的候选药物的最佳特征是它可以同时针对多个控制细胞分裂和生长激素的蛋白质,从而降低药物的耐药性。