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In silico ranking of phenolics for therapeutic effectiveness on cancer stem cells
BMC Bioinformatics ( IF 3 ) Pub Date : 2020-12-28 , DOI: 10.1186/s12859-020-03849-z
Monalisa Mandal 1 , Sanjeeb Kumar Sahoo 2 , Priyadarsan Patra 1 , Saurav Mallik 3 , Zhongming Zhao 3, 4
Affiliation  

Cancer stem cells (CSCs) have features such as the ability to self-renew, differentiate into defined progenies and initiate the tumor growth. Treatments of cancer include drugs, chemotherapy and radiotherapy or a combination. However, treatment of cancer by various therapeutic strategies often fail. One possible reason is that the nature of CSCs, which has stem-like properties, make it more dynamic and complex and may cause the therapeutic resistance. Another limitation is the side effects associated with the treatment of chemotherapy or radiotherapy. To explore better or alternative treatment options the current study aims to investigate the natural drug-like molecules that can be used as CSC-targeted therapy. Among various natural products, anticancer potential of phenolics is well established. We collected the 21 phytochemicals from phenolic group and their interacting CSC genes from the publicly available databases. Then a bipartite graph is constructed from the collected CSC genes along with their interacting phytochemicals from phenolic group as other. The bipartite graph is then transformed into weighted bipartite graph by considering the interaction strength between the phenolics and the CSC genes. The CSC genes are also weighted by two scores, namely, DSI (Disease Specificity Index) and DPI (Disease Pleiotropy Index). For each gene, its DSI score reflects the specific relationship with the disease and DPI score reflects the association with multiple diseases. Finally, a ranking technique is developed based on PageRank (PR) algorithm for ranking the phenolics. We collected 21 phytochemicals from phenolic group and 1118 CSC genes. The top ranked phenolics were evaluated by their molecular and pharmacokinetics properties and disease association networks. We selected top five ranked phenolics (Resveratrol, Curcumin, Quercetin, Epigallocatechin Gallate, and Genistein) for further examination of their oral bioavailability through molecular properties, drug likeness through pharmacokinetic properties, and associated network with CSC genes. Our PR ranking based approach is useful to rank the phenolics that are associated with CSC genes. Our results suggested some phenolics are potential molecules for CSC-related cancer treatment.

中文翻译:

酚类化合物对癌症干细胞治疗效果的计算机排名

癌症干细胞(CSC)具有自我更新、分化为特定子代以及启动肿瘤生长等能力。癌症的治疗包括药物、化疗和放疗或组合疗法。然而,通过各种治疗策略治疗癌症常常会失败。一个可能的原因是CSCs具有类似干细胞的性质,使其更加动态和复杂,并可能导致治疗抵抗。另一个限制是与化疗或放疗相关的副作用。为了探索更好或替代的治疗方案,当前的研究旨在研究可用作 CSC 靶向治疗的天然药物样分子。在各种天然产物中,酚类物质的抗癌潜力是众所周知的。我们从公开数据库中收集了 21 种酚基植物化学物质及其相互作用的 CSC 基因。然后,根据收集的 CSC 基因及其相互作用的酚基和其他植物化学物质构建二分图。然后通过考虑酚类和CSC基因之间的相互作用强度将二分图转化为加权二分图。CSC基因也通过两个分数进行加权,即DSI(疾病特异性指数)和DPI(疾病多效性指数)。对于每个基因,其DSI评分反映了与疾病的特定关系,DPI评分反映了与多种疾病的关联。最后,基于PageRank(PR)算法开发了一种对酚类物质进行排名的排名技术。我们收集了 21 种酚类植物化学物质和 1118 个 CSC 基因。排名靠前的酚类物质通过其分子和药代动力学特性以及疾病关联网络进行评估。我们选择了排名前五的酚类物质(白藜芦醇、姜黄素、槲皮素、表没食子儿茶素没食子酸酯和染料木黄酮),通过分子特性、药代动力学特性的药物相似性以及与 CSC 基因的相关网络进一步检查其口服生物利用度。我们基于 PR 排名的方法对于对与 CSC 基因相关的酚类物质进行排名非常有用。我们的结果表明一些酚类物质是 CSC 相关癌症治疗的潜在分子。
更新日期:2020-12-28
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