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基于 DNA 拓扑异构酶 I 的靶点,运用计算筛选和中药(TCM)化合物的分子对接,设计潜在的抗癌药物。

Computational screening and molecular docking of compounds from Traditional Chinese Medicine (TCM) by targeting DNA topoisomerase I to design potential anticancer drugs.

机构信息

Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh.

出版信息

PLoS One. 2024 Sep 12;19(9):e0310364. doi: 10.1371/journal.pone.0310364. eCollection 2024.

Abstract

Each year thousands of people suffer across the globe due to higher cancer incidence and mortality rates. Additionally, the treatment option for cancer patients is also costly, and often cancer drugs suffer from lower efficacy with more side effects. The DNA topoisomerase can function as an established cancer target because Human Topoisomerase (Top1) regulates genetic transcription during the post-mitotic phase and plays a critical role in DNA supercoiling during replication and repair. Therefore, during drug therapy, blocking the Top1 may be crucial for inhibiting the proliferation of cancer cells. Here, the TCM (traditional Chinese medicine) compounds have been screened through the virtual screening. The Chinese medicine library's virtual screening process made it possible to narrow down the compound list to 29 compounds based on binding energy (-7.1 to -9.3Kcal/mol), while following Lipniski filtering, MM/PB (GB) SA filtering was used to screen the remaining 22 compounds and the top four compounds were chosen based on binding free energy. Here, the four compounds; CID-65752 (T2972: Rutaecarpine), CID-5271805 (T4S2126: Ginkgetin), CID-9817839 (T2S2335: Dehydroevodiamine) and CID-51106 (T3054: Daurisoline) had comparatively higher binding energy of -8.2, -8.5, -8.3 and -8.2 respectively during molecular docking than other compounds. Among these four compounds, no toxic profile of the two screened compounds; CID-5271805 and CID-9817839 was found in ADMET filtering. Moreover, the SASA (solvent accessible surface area), Rg (radius of gyrations), RMSD (root mean square deviation), and RMSF (root mean square fluctuation) profile of the drug-protein complex reveals the stability and rigidity of the compounds in molecular dynamics simulation study. However, these studies need to be validated in experimental approaches to develop more potent and effective cancer drugs.

摘要

每年,全球都有数千人因癌症发病率和死亡率上升而受苦。此外,癌症患者的治疗选择也很昂贵,而且癌症药物往往疗效较低,副作用更多。DNA 拓扑异构酶可以作为一个既定的癌症靶点,因为人类拓扑异构酶(Top1)在有丝分裂后阶段调节基因转录,并在复制和修复过程中发挥关键作用,使 DNA 超螺旋化。因此,在药物治疗中,阻断 Top1 可能对抑制癌细胞增殖至关重要。在这里,通过虚拟筛选对中药(TCM)化合物进行了筛选。中药库的虚拟筛选过程使得基于结合能(-7.1 至-9.3Kcal/mol)将化合物列表缩小到 29 种化合物成为可能,在遵循 Lipniski 过滤之后,使用 MM/PB(GB)SA 过滤筛选其余 22 种化合物,并根据结合自由能选择前四种化合物。在这里,四种化合物;CID-65752(T2972:Rutaecarpine)、CID-5271805(T4S2126:Ginkgetin)、CID-9817839(T2S2335:Dehydroevodiamine)和 CID-51106(T3054:Daurisoline)在分子对接中具有相对较高的结合能,分别为-8.2、-8.5、-8.3 和-8.2。在这四种化合物中,在 ADMET 过滤中没有发现两种筛选化合物 CID-5271805 和 CID-9817839 的毒性特征。此外,药物-蛋白质复合物的 SASA(溶剂可及表面积)、Rg(回旋半径)、RMSD(均方根偏差)和 RMSF(均方根波动)谱揭示了化合物在分子动力学模拟研究中的稳定性和刚性。然而,这些研究需要在实验方法中进行验证,以开发更有效和有效的癌症药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2891/11392414/8e9f4a757098/pone.0310364.g001.jpg

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