Computational Intelligence and Bioinformatics Lab, Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India.
Computational Intelligence and Bioinformatics Lab, Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India; Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi 110067, India.
Int J Biol Macromol. 2024 Sep;276(Pt 1):133872. doi: 10.1016/j.ijbiomac.2024.133872. Epub 2024 Jul 15.
Lung Cancer (LC) is among the most death-causing cancers, has caused the most destruction and is a gender-neutral cancer, and WHO has kept this cancer on its priority list to find the cure. We have used high-throughput virtual screening, standard precision docking, and extra precise docking for extensive screening of Drug Bank compounds, and the uniqueness of this study is that it considers multiple protein targets of prognosis and metastasis of LC. The docking and MM\GBSA calculation scores for the Tiaprofenic acid (DB01600) against all ten proteins range from -8.422 to -5.727 kcal/mol and - 47.43 to -25.72 kcal/mol, respectively. Also, molecular fingerprinting helped us to understand the interaction pattern of Tiaprofenic acid among all the proteins. Further, we extended our analysis to the molecular dynamic simulation in a neutralised SPC water medium for 100 ns. We analysed the root mean square deviation, fluctuations, and simulative interactions among the protein, ligand, water molecules, and protein-ligand complexes. Most complexes have shown a deviation of <2 Å as cumulative understanding. Also, the fluctuations were lesser, and only a few residues showed the fluctuation with a huge web of interaction between the protein and ligand, providing an edge that supports that the protein and ligand complexes were stable. In the MTT-based Cell Viability Assay, Tiaprofenic Acid exhibited concentration-dependent anti-cancer efficacy against A549 lung cancer cells, significantly reducing viability at 100 μg/mL. These findings highlight its potential as a therapeutic candidate, urging further exploration into the underlying molecular mechanisms for lung cancer treatment.
肺癌(LC)是最致命的癌症之一,造成的破坏最大,而且是一种不分性别的癌症,世界卫生组织一直将这种癌症列入优先清单,以寻找治愈方法。我们使用高通量虚拟筛选、标准精确对接和额外精确对接对 Drug Bank 化合物进行了广泛筛选,这项研究的独特之处在于它考虑了 LC 预后和转移的多个蛋白靶点。Tiaprofenic acid(DB01600)与所有十种蛋白的对接和 MM\GBSA 计算评分范围分别为-8.422 至-5.727 kcal/mol 和-47.43 至-25.72 kcal/mol。此外,分子指纹图谱帮助我们了解了 Tiaprofenic acid 与所有蛋白之间的相互作用模式。此外,我们将分析扩展到中性 SPC 水中 100 ns 的分子动力学模拟。我们分析了均方根偏差、波动和蛋白质、配体、水分子和蛋白质-配体复合物之间的模拟相互作用。大多数复合物都表现出 <2 Å 的偏差,作为累积的理解。此外,波动较小,只有少数残基表现出巨大的波动,蛋白质和配体之间存在广泛的相互作用,这为支持蛋白质和配体复合物的稳定性提供了优势。在 MTT 基于的细胞活力测定中,Tiaprofenic Acid 对 A549 肺癌细胞表现出浓度依赖性的抗癌功效,在 100 μg/mL 时显著降低了细胞活力。这些发现强调了它作为治疗候选物的潜力,促使进一步探索治疗肺癌的潜在分子机制。