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Computational Identification of Potential Dipeptidyl Peptidase (DPP)-IV Inhibitors: Structure Based Virtual Screening, Molecular Dynamics Simulation and Knowledge based SAR Studies
Journal of Molecular Structure ( IF 4.0 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.molstruc.2020.129006
Virendra Nath , Manish Ramchandani , Neeraj Kumar , Rohini Agrawal , Vipin Kumar

Abstract Type 2 Diabetes mellitus (T2DM) is a globally leading metabolic problem with increased morbidity and mortality. Current medication therapies in the market to control diabetes are not sufficient and therefore, there is further need to develop more selective and effective treatment approaches. Inhibition of Dipeptidyl-peptidase-IV (DPP-IV) enzyme may serve as an interesting target for developing novel anti-diabetic drug candidate. In the present study, hierarchical virtual screening of drug like compounds was done followed by molecular dynamics simulation and knowledge-based structure-activity relation (SAR) study in order to retrieve hit compound as prospective inhibitors of DPP-IV enzyme. Important amino acid residues present in the active target site were acknowledged as vital and were also found to have similar interactions with the potential hits. Further, in silico technique was undertaken to identify ubiquitous promising hits against DPP-IV enzyme and this was followed by calculation of binding energy and absorption, distribution, metabolism, excretion (ADME) prediction that could possibly support their pharmacokinetic prospective. Furthermore, stability study using molecular dynamics simulation of protein complex was accomplished with the most capable targeted hit established in the present study. In the end, comparative analysis of 3-dimensional binding pose, orientation and planar structure of the potential retrieved hit was done with marketed drugs (alogliptin and sitagliptin) in order to develop knowledge-based structure-activity relationship, which proved the successful designing of DPP-IV enzyme inhibitors.

中文翻译:

潜在二肽基肽酶 (DPP)-IV 抑制剂的计算鉴定:基于结构的虚拟筛选、分子动力学模拟和基于知识的 SAR 研究

摘要 2 型糖尿病 (T2DM) 是一种全球领先的代谢问题,发病率和死亡率都在增加。目前市场上控制糖尿病的药物疗法还不够,因此,进一步需要开发更具选择性和更有效的治疗方法。抑制二肽基-肽酶-IV (DPP-IV) 酶可以作为开发新型抗糖尿病候选药物的有趣目标。在本研究中,通过分子动力学模拟和基于知识的结构-活性关系 (SAR) 研究对类药物化合物进行分层虚拟筛选,以检索作为 DPP-IV 酶的前瞻性抑制剂的命中化合物。存在于活性靶位点的重要氨基酸残基被认为是至关重要的,并且还发现与潜在命中具有类似的相互作用。此外,采用计算机技术来识别普遍存在的针对 DPP-IV 酶的有希望的命中,然后计算结合能和吸收、分布、代谢、排泄 (ADME) 预测,这可能支持其药代动力学前景。此外,使用蛋白质复合物的分子动力学模拟的稳定性研究是通过本研究中建立的最有能力的靶向命中完成的。最后,3维绑定姿势对比分析,
更新日期:2021-01-01
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