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基于 Garcinia 笼状紫檀烷衍生物的抗癌活性的虚拟筛选、对接、ADMET 和系统药理学研究。

Virtual screening, Docking, ADMET and System Pharmacology studies on Garcinia caged Xanthone derivatives for Anticancer activity.

机构信息

Metabolic & Structural Biology Department, CSIR-Central Institute of Medicinal & Aromatic Plants, P.O.-CIMAP, Lucknow, 226015, Uttar Pradesh, India.

Academy of Scientific & Innovative Research (AcSIR), CSIR-CIMAP Campus, Lucknow, 226015, Uttar Pradesh, India.

出版信息

Sci Rep. 2018 Apr 3;8(1):5524. doi: 10.1038/s41598-018-23768-7.

Abstract

Caged xanthones are bioactive compounds mainly derived from the Garcinia genus. In this study, a structure-activity relationship (SAR) of caged xanthones and their derivatives for anticancer activity against different cancer cell lines such as A549, HepG2 and U251 were developed through quantitative (Q)-SAR modeling approach. The regression coefficient (r), internal cross-validation regression coefficient (q) and external cross-validation regression coefficient (pred_r) of derived QSAR models were 0.87, 0.81 and 0.82, for A549, whereas, 0.87, 0.84 and 0.90, for HepG2, and 0.86, 0.83 and 0.83, for U251 respectively. These models were used to design and screened the potential caged xanthone derivatives. Further, the compounds were filtered through the rule of five, ADMET-risk and synthetic accessibility. Filtered compounds were then docked to identify the possible target binding pocket, to obtain a set of aligned ligand poses and to prioritize the predicted active compounds. The scrutinized compounds, as well as their metabolites, were evaluated for different pharmacokinetics parameters such as absorption, distribution, metabolism, excretion, and toxicity. Finally, the top hit compound 1G was analyzed by system pharmacology approaches such as gene ontology, metabolic networks, process networks, drug target network, signaling pathway maps as well as identification of off-target proteins that may cause adverse reactions.

摘要

笼状紫檀烷类化合物是一类主要来源于藤黄属植物的生物活性化合物。在这项研究中,通过定量构效关系(QSAR)建模方法,研究了笼状紫檀烷类化合物及其衍生物对不同癌细胞系(如 A549、HepG2 和 U251)的抗癌活性的构效关系(SAR)。所得 QSAR 模型对 A549 的回归系数(r)、内部交叉验证回归系数(q)和外部交叉验证回归系数(pred_r)分别为 0.87、0.81 和 0.82,对 HepG2 分别为 0.87、0.84 和 0.90,对 U251 分别为 0.86、0.83 和 0.83。这些模型被用于设计和筛选潜在的笼状紫檀烷类衍生物。此外,还通过五规则、ADMET 风险和合成可及性对化合物进行了筛选。筛选出的化合物然后进行对接,以确定可能的靶标结合口袋,获得一组对齐的配体构象,并对预测的活性化合物进行优先级排序。然后对仔细筛选的化合物及其代谢物进行了不同的药代动力学参数评估,如吸收、分布、代谢、排泄和毒性。最后,通过系统药理学方法(如基因本体、代谢网络、过程网络、药物靶标网络、信号通路图谱以及鉴定可能引起不良反应的非靶点蛋白)对 top hit 化合物 1G 进行了分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6023/5883056/4d6f16571c9f/41598_2018_23768_Fig1_HTML.jpg

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