Suppr超能文献

基于多重采样的对接揭示咪唑烷基脲作为肺癌的多靶点抑制剂:一项多模拟及研究后的优化。

Multisampling-based docking reveals Imidazolidinyl urea as a multitargeted inhibitor for lung cancer: an optimisation followed multi-simulation and study.

作者信息

Ahmad Shaban, Singh Vijay, Gautam Hemant K, Raza Khalid

机构信息

Department of Computer Science, Jamia Millia Islamia, New Delhi, India.

Immunology and Infectious Disease, Institute of Genomics and Integrative Biology (IGIB), New Delhi, India.

出版信息

J Biomol Struct Dyn. 2024 Mar;42(5):2494-2511. doi: 10.1080/07391102.2023.2209673. Epub 2023 May 8.

Abstract

Lung Cancer is one of the deadliest cancers, responsible for more than 1.80 million deaths annually worldwide, and it is on the priority list of WHO. In the current scenario, when cancer cells become resistant to the drug, making it less effective leaves the patient in vulnerable conditions. To overcome this situation, researchers are constantly working on new drugs and medications that can help fight drug resistance and improve patients' outcomes. In this study, we have taken five main proteins of lung cancer, namely RSK4 N-terminal kinase, guanylate kinase, cyclin-dependent kinase 2, kinase CK2 holoenzyme, tumour necrosis factor-alpha and screened the prepared Drug Bank library with 1,55,888 compounds against all using three Glide-based docking algorithms namely HTVS, standard precision and extra precise with a docking score ranging from -5.422 to -8.432 Kcal/mol. The poses were filtered with the MM\GBSA calculations, which helped to identify Imidazolidinyl urea CHNO (DB14075) as a multitargeted inhibitor for lung cancer, validated with advanced computations like ADMET, interaction pattern fingerprints, and optimised the compound with Jaguar, producing satisfied relative energy. All five complexes were performed with MD Simulation for 100 ns with NPT ensemble class, producing cumulative deviation and fluctuations < 2 Å and a web of intermolecular interaction, making the complexes stable. Further, the in-vitro analysis for morphological imaging, Annexin V/PI FACS assay, ROS and MMP analysis caspase3//7 activity were performed on the A549 cell line producing promising results and can be an option to treat lung cancer at a significantly cheaper state.Communicated by Ramaswamy H. Sarma.

摘要

肺癌是最致命的癌症之一,全球每年有超过180万人死于肺癌,它在世卫组织的优先事项清单上。在当前情况下,当癌细胞对药物产生耐药性时,药物疗效降低会使患者处于脆弱状态。为克服这种情况,研究人员不断致力于研发能帮助对抗耐药性并改善患者预后的新药和药物。在本研究中,我们选取了肺癌的五种主要蛋白质,即核糖体S6激酶4 N端激酶、鸟苷酸激酶、细胞周期蛋白依赖性激酶2、酪蛋白激酶2全酶、肿瘤坏死因子-α,并使用基于Glide的三种对接算法,即高通量虚拟筛选(HTVS)、标准精度和高精度,对制备的包含155888种化合物的药物库进行筛选,对接分数范围为-5.422至-8.432千卡/摩尔。通过MM\GBSA计算对构象进行筛选,这有助于确定咪唑烷基脲CHNO(DB14075)为肺癌的多靶点抑制剂,并通过如ADMET、相互作用模式指纹等先进计算进行验证,然后用Jaguar对该化合物进行优化,产生令人满意的相对能量。所有五个复合物均在NPT系综类别下进行了100纳秒的分子动力学模拟,产生的累积偏差和波动<2埃以及分子间相互作用网络,使复合物稳定。此外,对A549细胞系进行了形态学成像、膜联蛋白V/碘化丙啶流式细胞术分析、活性氧和线粒体膜电位分析、半胱天冬酶3/7活性的体外分析,结果很有前景,并且可以成为以显著更低成本治疗肺癌的一种选择。由拉马斯瓦米·H·萨尔马传达。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验