Molecular docking and molecular dynamic simulation of phytochemical derived compounds as potential anti cancer agent against tyrosine kinase

Siddharth Bhatt, D. Patel, S. Desai, D. Meshram
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引用次数: 1

Abstract

There is a continuous requirement to develop novel, safe, effective and affordable anti-cancer drugs because Cancer is a serious disease at current situation. A huge number of patients die annually due to cancer disease.  Phytochemical are the secondary metabolites of medicinal plants and significantly used in conventional cancer research.  Bioactive phytochemical is favored as they claim differentially on cancer cell only without altering normal cell. Carcinogenesis is an intricate process and includes multifold signaling procedures. Phytochemical are pleiotropic in nature, function and target these events in multiple manners so they are considered as most appropriate candidate for drug development. The aim of the present research was to find out the anti-cancer activity of the phytochemical constituents through computer aided drug design approach. In this experiment, we have find total 42 natural compounds with anti-cancer activity against the cancer target 1QCF tyrosine kinase. The data set comprising of phytochemical compounds was used for virtual screening and molecular docking in PyRx software. Along with screened compound, hit compound Carnosic acid was further docked to confirm the binding mode and confirmed the effective inhibition of 1QCF and anticancer activity. Molecular dynamic simulation studies were done to confirm the stability of the protein and ligand complex during a simulation. Parameters like RMSD, RMSF, and radius of gyration were experiential to understand the fluctuations. Protein-ligand interaction studies also expose that enough hydrogen and hydrophobic bonds are present to validate our results. Our study suggests that the potential use of Carnosic acid can come out as a potential candidate and in turn prevent cancer.
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植物化学衍生化合物作为酪氨酸激酶潜在抗癌剂的分子对接与分子动力学模拟
癌症是一种严重的疾病,因此不断要求开发出新颖、安全、有效、价格合理的抗癌药物。每年有大量的病人死于癌症。植物化学物质是药用植物的次生代谢产物,在传统的癌症研究中有着重要的应用。具有生物活性的植物化学物质受到青睐,因为它们只对癌细胞有不同的作用,而不会改变正常细胞。癌变是一个复杂的过程,包括多重信号过程。植物化学具有多效性,以多种方式作用和靶向这些事件,因此它们被认为是最合适的药物开发候选者。本研究的目的是通过计算机辅助药物设计方法来发现植物化学成分的抗癌活性。在本实验中,我们共发现了42种针对癌症靶点1QCF酪氨酸激酶具有抗癌活性的天然化合物。在PyRx软件中,利用包含植物化学成分的数据集进行虚拟筛选和分子对接。与筛选的化合物一起,进一步对接命中的化合物鼠尾草酸,确认其结合模式,证实其对1QCF的有效抑制和抗癌活性。在模拟过程中进行了分子动力学模拟研究,以证实蛋白质和配体复合物的稳定性。RMSD, RMSF和旋转半径等参数是经验的,以了解波动。蛋白质-配体相互作用的研究也表明,存在足够的氢键和疏水键来验证我们的结果。我们的研究表明,鼠尾草酸的潜在用途可以作为潜在的候选者,从而预防癌症。
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