Chidambaram Kumarappan
Department of Pharmacology and Toxicology, College of Pharmacy, Al-Qara Campus, King Khalid University, Asir Province, Abha 61421, Saudi Arabia.
Life (Basel). 2023 Apr 5;13(4):952. doi: 10.3390/life13040952.
Alzheimer is a severe memory and cognitive impairment neurodegenerative disease that is the most common cause of dementia worldwide and characterized by the pathological accumulation of tau protein and amyloid-beta peptides. In this study, we have developed E-pharmacophore modeling to screen the eMolecules database with the help of a reported co-crystal structure bound with Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1 (BACE-1). Flumemetamol, florbetaben, and florbetapir are currently approved drugs for use in the clinical diagnosis of Alzheimer's disease. Despite the benefits of commercially approved drugs, there is still a need for novel diagnostic agents with enhanced physicochemical and pharmacokinetic properties compared to those currently used in clinical practice and research. In the E-pharmacophore modeling results, it is revealed that two aromatic rings (R19, R20), one donor (D12), and one acceptor (A8) are obtained, and also that similar pharmacophoric features of compounds are identified from pharmacophore-based virtual screening. The identified screened hits were filtered for further analyses using structure-based virtual screening and MM/GBSA. From the analyses, top hits such as ZINC39592220 and en1003sfl.46293 are selected based on their top docking scores (-8.182 and -7.184 Kcal/mol, respectively) and binding free energy (-58.803 and -56.951 Kcal/mol, respectively). Furthermore, a molecular dynamics simulation and MMPBSA study were performed, which revealed admirable stability and good binding free energy throughout the simulation period. Moreover, Qikprop results revealed that the selected, screened hits have good drug-likeness and pharmacokinetic properties. The screened hits ZINC39592220 and en1003sfl.46293 could be used to develop drug molecules against Alzheimer's disease.
阿尔茨海默病是一种严重的记忆和认知障碍神经退行性疾病,是全球痴呆症最常见的病因,其特征是tau蛋白和β-淀粉样肽的病理性积累。在本研究中,我们借助已报道的与β-位点淀粉样前体蛋白裂解酶1(BACE-1)结合的共晶体结构,开发了电子药效团模型来筛选电子分子数据库。氟美他莫、氟贝他班和氟代硼替吡是目前批准用于阿尔茨海默病临床诊断的药物。尽管商业批准的药物有诸多益处,但仍需要开发新型诊断剂,其理化性质和药代动力学性质比目前临床实践和研究中使用的药物有所增强。在电子药效团模型结果中,发现了两个芳香环(R19、R20)、一个供体(D12)和一个受体(A8),并且从基于药效团的虚拟筛选中识别出了化合物的相似药效特征。使用基于结构的虚拟筛选和MM/GBSA对识别出的筛选命中物进行进一步分析筛选。通过分析,根据它们的最高对接分数(分别为-8.182和-7.184千卡/摩尔)和结合自由能(分别为-58.803和-56.951千卡/摩尔),选择了如ZINC39592220和en1003sfl.46293等顶级命中物。此外,进行了分子动力学模拟和MMPBSA研究,结果表明在整个模拟期间具有令人满意的稳定性和良好的结合自由能。此外,Qikprop结果显示,所选的筛选命中物具有良好的类药性质和药代动力学性质。筛选命中物ZINC39592220和en1003sfl.46293可用于开发抗阿尔茨海默病的药物分子。