Abstract:
Alzheimer\'s disease (AD) is the most prevalent type of dementia caused by the accumulation of amyloid beta (Aβ) peptides. The extracellular deposition of Aβ peptides in human AD brain causes neuronal death. Therefore, it has been found that Aβ peptide degradation is a possible therapeutic target for AD. CathD has been known to breakdown amyloid beta peptides. However, the structural role of CathD is not yet clear. Hence, for the purpose of gaining a deeper comprehension of the structure of CathD, the present computational investigation was performed using virtual screening technique to predict CathD\'s active site residues and substrate binding mode. Ligand-based virtual screening was implemented on small molecules from ZINC database against crystal structure of CathD. Further, molecular docking was utilised to investigate the binding mechanism of CathD with substrates and virtually screened inhibitors. Localised compounds obtained through screening performed by PyRx and AutoDock 4.2 with CathD receptor and the compounds having highest binding affinities were picked as; ZINC00601317, ZINC04214975 and ZINCC12500925 as our top choices. The hydrophobic residues Viz. Gly35, Val31, Thr34, Gly128, Ile124 and Ala13 help stabilising the CathD-ligand complexes, which in turn emphasises substrate and inhibitor selectivity. Further, MM-GBSA approach has been used to calculate binding free energy between CathD and selected compounds. Therefore, it would be beneficial to understand the active site pocket of CathD with the assistance of these discoveries. Thus, the present study would be helpful to identify active site pocket of CathD, which could be beneficial to develop novel therapeutic strategies for the AD.
摘要:
阿尔茨海默病(AD)是由淀粉样β(Aβ)肽积累引起的最常见的痴呆类型。人AD脑中Aβ肽的细胞外沉积导致神经元死亡。因此,已经发现Aβ肽降解是AD的可能的治疗靶标。已知CathD分解淀粉样β肽。然而,CathD的结构作用尚不清楚。因此,为了更深入地理解CathD的结构,本计算研究采用虚拟筛选技术预测CathD的活性位点残基和底物结合模式。针对CathD的晶体结构,对来自ZINC数据库的小分子实施基于配体的虚拟筛选。Further,利用分子对接来研究CathD与底物和几乎筛选的抑制剂的结合机制。通过PyRx和AutoDock4.2与CathD受体进行筛选获得的局部化合物和具有最高结合亲和力的化合物被选为;ZINC00601317、ZINC04214975和ZINCC12500925作为我们的首选。疏水性残基Viz.Gly35,Val31,Thr34,Gly128,Ile124和Ala13有助于稳定CathD-配体复合物,这反过来又强调了底物和抑制剂的选择性。Further,MM-GBSA方法已用于计算CathD与所选化合物之间的结合自由能。因此,在这些发现的帮助下,了解CathD的活性位点口袋将是有益的。因此,本研究将有助于确定CathD的活性位点口袋,这可能有利于开发新的AD治疗策略。