Department of Computer Science, Jamia Millia Islamia, New Delhi, India.
Computational Structural Biology Lab, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.
J Biomol Struct Dyn. 2023 Nov;41(19):9770-9786. doi: 10.1080/07391102.2022.2146202. Epub 2022 Nov 15.
The cervix is the lowermost part of the uterus that connects to the vagina, and cervical cancer is a malignant cervix tumour. One of this cancer's most important risk factors is HPV infection. In the approach to finding an effective treatment for this disease, various works have been done around genomics and drug discovery. Finding the major altered genes was one of the most significant studies completed in the field of cervical cancer by TCGA (The Cancer Genome Atlas), and these genes are TGFBR2, MED1, ERBB3, CASP8, and HLA-A. The greatest genomic alterations were found in the PI3K/MAPK and TGF-Beta signalling pathways, suggesting that numerous therapeutic targets may come from these pathways in the future. We, therefore, conducted a combined enrichment analysis of genes gathered from various works of literature for this study. The final six key genes from the list were obtained after enrichment analysis using GO, KEGG, and Reactome methods. The six proteins against the identified genes were then subjected to a docking-based screening against a library of 6,87,843 prepared natural compounds from the ZINC15 database. The most stable compound was subsequently discovered through virtual screening to be the natural substance Quinic acid, which also had the highest binding affinity for all six proteins and a better docking score. To examine their stability, the study was extended to MM/GBSA and MD simulations on the six docked proteins, and comparative docking-based calculations led us to identify the Quinic Acid as a multitargeted compound. The overall deviation of the compound was less than 2 Å for all the complexes considered best for the biological molecules, and the simulation interaction analysis reveals a huge web of interaction during the simulation.Communicated by Ramaswamy H. Sarma.
子宫颈是连接阴道的子宫的最低部分,宫颈癌是一种恶性宫颈肿瘤。这种癌症最重要的危险因素之一是 HPV 感染。在寻找这种疾病的有效治疗方法的过程中,在基因组学和药物发现方面做了各种工作。TCGA(癌症基因组图谱)在宫颈癌领域完成的最重要的研究之一是发现主要的改变基因,这些基因是 TGFBR2、MED1、ERBB3、CASP8 和 HLA-A。最大的基因组改变发生在 PI3K/MAPK 和 TGF-β信号通路中,这表明未来可能会有许多治疗靶点来自这些通路。因此,我们对本研究中从各种文献中收集的基因进行了联合富集分析。通过 GO、KEGG 和 Reactome 方法进行富集分析后,从列表中获得了最终的六个关键基因。然后,针对鉴定出的基因,对这六个蛋白质进行基于对接的筛选,针对来自 ZINC15 数据库的 687843 个天然化合物库进行筛选。通过虚拟筛选,我们发现最稳定的化合物是天然物质奎尼酸,它对所有六个蛋白质都有最高的结合亲和力和更好的对接分数。为了检查它们的稳定性,研究扩展到了 MM/GBSA 和 MD 对六个对接蛋白的模拟,基于对接的比较计算使我们确定奎尼酸是一种多靶化合物。对于所有被认为最适合生物分子的复合物,化合物的整体偏差都小于 2 Å,模拟相互作用分析揭示了在模拟过程中存在巨大的相互作用网络。由 Ramaswamy H. Sarma 传达。