基于L1000数据集筛选骨质疏松症的潜在治疗化合物

Screening of potential therapeutic compounds for osteoporosis based on L1000 database

目的:应用L1000微干扰数据集筛选治疗骨质疏松症的化合物,通过多种生物信息学的方法评价及细胞学活性验证,旨在发现新的骨质疏松症治疗药物。方法:在GEO数据库中检索与骨质疏松症相关的数据,利用R语言的limma包对数据集进行基因表达量的差异分析;通过MetaScape数据平台对差异表达基因进行通路富集分析。利用分析得到的骨质疏松症差异基因表达谱,在“连接图”数据库的L1000数据集中,匹配潜在治疗化合物。通过Autodock_Vina软件将匹配化合物与骨代谢靶点进行分子对接研究,利用pkCSM数据库对匹配化合物的ADMET(吸收、分布、代谢、排泄、毒性)特征进行计算分析,通过细胞增殖活性实验对候选化合物的活性进行研究。结果:分析骨质疏松症的表达谱数据集,共获得195个与骨质疏松症相关的差异表达基因,表达量显著上调的基因有127个,表达量显著下调的基因有68个;差异表达基因富集的GO生物过程共有146个;富集的KEGG信号通路共有9条,富集的Reactome基因集共有9个。在L1000数据集中匹配到潜在治疗化合物共10个,分别为己烯雌酚、PLX-4720、美西林、KU-C103428N、土大黄苷、马拉韦罗、奎宁、MST-312、利培酮、CO-102862。通过分子对接研究,发现匹配化合物具有多靶点的特性,与化合物对接活性较好的主要有碳酸酐酶Ⅱ(CAⅡ)、孕酮受体(PGR)、雌激素受体β(ERβ)、骨形态发生蛋白2(BMP2)等骨质疏松症的靶点。通过pkCSM数据库对潜在治疗化合物的ADMET性质计算表明,美西林具有较好的ADME性能和较低的毒性,综合评价较好;细胞增殖实验结果显示20μg/mL的美西林对成骨细胞的增殖效果最为显著。结论:通过L1000数据集,筛选得到的骨质疏松症治疗候选化合物美西林,具有较好的ADMET特征和促成骨细胞增殖的活性。

Objective:The L1000 micro-interference data set was used to screen compounds for the treatment of osteoporosis,and the evaluation and cytological activity verification by multiple biological information methods were conducted,aiming to discover new osteoporosis treatment drugs.Methods:The data related to osteoporosis(OP)were retrieved in the GEO(Gene Expression Omnibus)database,and the difference in gene expression levels on the datasets was analyzed using limma package in R language.Pathway enrichment analysis of differential genes was performed using MetaScape data platform.The resulting differential OP gene expression profiles were analyzed to match potential OP therapeutic compounds in the L1000 dataset of the Connectivity Map database.The molecular docking study of the matching compounds and bone metabolism targets was conducted by Autodock_Vina software,and the ADMET(absorption,distribution,metabolism,excretion,and toxicity)characteristics of the matching compounds were calculated and analyzed by using pkCSM database.The activity of the candidate compound was studied by a cell proliferative activity experiment.Results:After analyzing the dataset of osteoporosis expression profile,195 differential genes related to osteoporosis were obtained,including 127 genes with significantly up-regulated expression and 68 genes with significantly down-regulated expression.There were 146 GO Biological Processes with differential gene enrichment;There were nine enriched KEGG signaling pathways and nine enriched Reactome Gene Sets.A total of 10 potential therapeutic compounds were matched in the L1000 dataset:diethylstilbestrol,PLX-4720,mezlocillin,KU-C103428N,rhapontin,maravir,quinine,MST-312,risperidone,and CO-102862.Through molecular docking studies,we found that the matching compounds have multi-target characteristics,and the main docking activities with the compounds are CAⅡ,PGR,ERβ,BMP2 and other OP targets.The ADMET properties of potential therapeutic compounds were calculated using the ADMET calculation module of the pkCSM database,which showed that mezlocillin had good ADME performance and low toxicity,with good comprehensive evaluation.Cell proliferation experiment showed that mezlocillin at 20μg/mL had the most significant effect on the proliferation of osteoblasts.Conclusion:The candidate OP therapeutic compound,mezlocillin,was screened from the L1000 data set with good ADMET characteristics and bone cell proliferation promoting activity.