目标:阿尔茨海默病(AD),一种极其进行性的神经退行性疾病是许多复杂的病理网络的融合。由于现有治疗剂在拮抗AD基础的多靶向病理途径中的适度功效,这种百年历史的疾病仍然是未满足的医学病症。鉴于AD特异性药物的缺乏,制定全面的研究策略,以设想疾病特定的目标,以引导和加快药物发现。然而,不断减少的批准率和对新化学实体批准的严格监管限制正在阻碍制药业进行从头研究。为了弥补AD药物研究中存在的空白,一个有希望的当代出路可能是药物再利用。这项药物再利用调查旨在通过一系列前卫的生物信息学和计算策略来设想AD特定靶标,并创建与入围靶标相关的药物库。
方法:三个AD特定数据集的转录组学分析。,GSE122063,GSE15222和GSE5281揭示了显着的差异表达基因(DEG)和随后的蛋白质-蛋白质相互作用(PPI)网络分析捕获了关键的AD靶标。稍后,通过I-TASSER对入围的缺乏X射线晶体结构的靶蛋白构建同源模型,并通过分子动力学模拟对构建的蛋白模型进行验证。Further,根据与各自标准药物的结构和副作用相似性,为入围目标创建药物库.最后,分子对接,进行了结合能计算和分子动力学研究,以解开所创建文库中药物与RGS4活性结合袋中氨基酸的相互作用。
结果:SST和RGS4入围了潜在的重要AD特异性目标,然而,较少探索的目标RGS4被考虑用于进一步的序贯分析.当通过Ramachandran图和ERRAT图验证时,为RGS4构建的同源性模型显示出最佳质量。随后的对接和分子动力学研究表明,三种药物证明了相当大的亲和力。,齐拉西酮,来自创建的药物库的美甲喹和美他沙酮,RGS4
结论:此虚拟分析预测了齐拉西酮的可再利用潜力,基于对关键AD特异性靶标RGS4的亲和力,美甲喹和美他沙酮抗AD。
OBJECTIVE: Alzheimer\'s Disease (AD), an extremely progressive neurodegenerative disorder is an amalgamation of numerous intricate pathological networks. This century old disease is still an unmet medical condition owing to the modest efficacy of existing therapeutic agents in antagonizing the multi-targeted pathological pathways underlying AD. Given the paucity in AD specific drugs, fabricating comprehensive research strategies to envision disease specific targets to channelize and expedite drug discovery are mandated. However, the dwindling approval rates and stringent regulatory constraints concerning the approval of a new chemical entity is daunting the pharmaceutical industries from effectuating de novo research. To bridge the existing gaps in AD drug research, a promising contemporary way out could be drug repurposing. This drug repurposing investigation is intended to envisage AD specific targets and create drug libraries pertinent to the shortlisted targets via a series of avant-garde bioinformatics and computational strategies.
METHODS: Transcriptomic analysis of three AD specific datasets viz., GSE122063, GSE15222 and GSE5281 revealed significant Differentially Expressed Genes (DEGs) and subsequent Protein-Protein Interactions (PPI) network analysis captured crucial AD targets. Later, homology model was constructed through I-TASSER for a shortlisted target protein which lacked X-ray crystallographic structure and the built protein model was validated by molecular dynamic simulations. Further, drug library was created for the shortlisted target based on structural and side effect similarity with respective standard drugs. Finally, molecular docking, binding energy calculations and molecular dynamics studies were carried out to unravel the interactions exhibited by drugs from the created library with amino acids in active binding pocket of
RGS4.
RESULTS: SST and
RGS4 were shortlisted as potentially significant AD specific targets, however, the less explored target
RGS4 was considered for further sequential analysis. Homology model constructed for
RGS4 displayed best quality when validated through Ramachandran plot and ERRAT plot. Subsequent docking and molecular dynamics studies showcased substantial affinity demonstrated by three drugs viz., Ziprasidone, Melfoquine and Metaxalone from the created drug libraries, towards
RGS4.
CONCLUSIONS: This virtual analysis forecasted the repurposable potential of Ziprasidone, Melfoquine and Metaxalone against AD based on their affinity towards RGS4, a key AD-specific target.