In Silico-Based Structural Prediction, Molecular Docking and ADMET Analysis of Novel Imidazo-Quinoline Derivatives as pf Purine Nucleoside Phosphorylase Inhibitors

Q3 Medicine
S. Kashaw, Chaitali Mallick, Mitali Mishra, Vivek Asati, Varsha Kashaw, R. Das
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引用次数: 0

Abstract

The prolonged antimalarial therapy with the marketed drug has developed multi-resistant strains of Plasmodium parasites that emerge as a consequential global problem. Therefore, designing new antimalarial agents is an exclusive solution to overcome the alarming situation. The integrated computational perspectives, such as pharmacophore mapping, 3D-QSAR and docking studies have been applied to improve the activity of the imidazo-quinoline scaffold. The best hypothesis AARRR_1 (Survival score 5.4609) obtained through pharmacophore mapping revealed that imidazo-quinoline scaffold is found to be vital for antimalarial activity. The significant CoMFA (q2 = 0.728, r2 = 0.909) and CoMSIA (q2 = 0.633, r2 = 0.729) models, developed by using molecular field analysis with the PLS method, showed good predictive ability with r2pred values of 0.9127 and 0.7726, respectively. Docking studies were performed using Schrodinger and GOLD software with the Plasmodium falciparum purine nucleoside phosphorylase enzyme (PDB ID-5ZNC) and results indicated that the imidazo-quinoline moiety facilitates the interaction with Tyr 160. In addition, some compounds are screened from the ZINC database based on structural requirements to verify the relevance of the research. Finally, designed molecules and ZINC database compounds were screened through the ADMET tool to evaluate pharmacokinetic and drug-likeness parameters. Thus, these exhaustive studies suggested that established models have good predictability and would help in the optimization of newly designed molecules that may lead to potent antimalarial activity for getting rid of resistance issues. Significant results have been obtained
新型咪唑啉衍生物作为嘌呤核苷磷酸化酶抑制剂的硅结构预测、分子对接和ADMET分析
这种上市药物的长期抗疟治疗已经产生了多耐药性疟原虫菌株,这已成为一个重大的全球问题。因此,设计新的抗疟药物是克服这一令人担忧的情况的唯一解决方案。药效团图谱、3D-QSAR和对接研究等综合计算方法已被应用于提高咪唑并喹啉支架的活性。通过药效团定位获得的最佳假设AARR_1(生存分数5.4609)表明咪唑并喹啉支架对抗疟活性至关重要。采用PLS方法进行分子场分析,建立了显著的CoMFA(q2=0.728,r2=0.909)和CoMSIA(q0=0.633,r2=0.729)模型,其r2pred值分别为0.9127和0.7726,显示出良好的预测能力。使用Schrodinger和GOLD软件与恶性疟原虫嘌呤核苷磷酸化酶(PDB ID-5ZNC)进行对接研究,结果表明咪唑并喹啉部分促进了与Tyr 160的相互作用。此外,根据结构要求从ZINC数据库中筛选了一些化合物,以验证研究的相关性。最后,通过ADMET工具筛选设计的分子和ZINC数据库化合物,以评估药代动力学和药物相似性参数。因此,这些详尽的研究表明,建立的模型具有良好的可预测性,有助于优化新设计的分子,这些分子可能会产生强大的抗疟活性,以消除耐药性问题。已取得重大成果
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来源期刊
CiteScore
1.70
自引率
0.00%
发文量
18
审稿时长
>12 weeks
期刊介绍: In recent years a breakthrough has occurred in our understanding of the molecular pathomechanisms of human diseases whereby most of our diseases are related to intra and intercellular communication disorders. The concept of signal transduction therapy has got into the front line of modern drug research, and a multidisciplinary approach is being used to identify and treat signaling disorders. The journal publishes timely in-depth reviews, research article and drug clinical trial studies in the field of signal transduction therapy. Thematic issues are also published to cover selected areas of signal transduction therapy. Coverage of the field includes genomics, proteomics, medicinal chemistry and the relevant diseases involved in signaling e.g. cancer, neurodegenerative and inflammatory diseases. Current Signal Transduction Therapy is an essential journal for all involved in drug design and discovery.
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