Mukerjee Nobendu, Das Anubhab, Jawarkar Rahul D, Maitra Swastika, Das Padmashree, Castrosanto Melvin A, Paul Soumyadip, Samad Abdul, Zaki Magdi E A, Al-Hussain Sami A, Masand Vijay H, Hasan Mohammad Mehedi, Bukhari Syed Nasir Abbas, Perveen Asma, Alghamdi Badrah S, Alexiou Athanasios, Kamal Mohammad Amjad, Dey Abhijit, Malik Sumira, Bakal Ravindra L, Abuzenadah Adel Mohammad, Ghosh Arabinda, Md Ashraf Ghulam
Department of Microbiology, Ramakrishna Mission Vivekananda Centenary College, Khardaha, India.
Department of Health Sciences, Novel Global Community Educational Foundation, Hebersham, NSW, Australia.
Front Aging Neurosci. 2022 Aug 22;14:878276. doi: 10.3389/fnagi.2022.878276. eCollection 2022.
Alzheimer's disease (AD) is a severe neurodegenerative disorder of the brain that manifests as dementia, disorientation, difficulty in speech, and progressive cognitive and behavioral impairment. The emerging therapeutic approach to AD management is the inhibition of β-site APP cleaving enzyme-1 (BACE1), known to be one of the two aspartyl proteases that cleave β-amyloid precursor protein (APP). Studies confirmed the association of high BACE1 activity with the proficiency in the formation of β-amyloid-containing neurotic plaques, the characteristics of AD. Only a few FDA-approved BACE1 inhibitors are available in the market, but their adverse off-target effects limit their usage. In this paper, we have used both ligand-based and target-based approaches for drug design. The QSAR study entails creating a multivariate GA-MLR (Genetic Algorithm-Multilinear Regression) model using 552 molecules with acceptable statistical performance ( = 0.82, = 0.81). According to the QSAR study, the activity has a strong link with various atoms such as aromatic carbons and ring Sulfur, acceptor atoms, sp2-hybridized oxygen, etc. Following that, a database of 26,467 food compounds was primarily used for QSAR-based virtual screening accompanied by the application of the Lipinski rule of five; the elimination of duplicates, salts, and metal derivatives resulted in a truncated dataset of 8,453 molecules. The molecular descriptor was calculated and a well-validated 6-parametric version of the QSAR model was used to predict the bioactivity of the 8,453 food compounds. Following this, the food compounds whose predicted activity (pKi) was observed above 7.0 M were further docked into the BACE1 receptor which gave rise to the Identification of 4-(3,4-Dihydroxyphenyl)-2-hydroxy-1H-phenalen-1-one (PubChem I.D: 4468; Food I.D: FDB017657) as a hit molecule (Binding Affinity = -8.9 kcal/mol, pKi = 7.97 nM, Ki = 10.715 M). Furthermore, molecular dynamics simulation for 150 ns and molecular mechanics generalized born and surface area (MMGBSA) study aided in identifying structural motifs involved in interactions with the BACE1 enzyme. Molecular docking and QSAR yielded complementary and congruent results. The validated analyses can be used to improve a drug/lead candidate's inhibitory efficacy against the BACE1. Thus, our approach is expected to widen the field of study of repurposing nutraceuticals into neuroprotective as well as anti-cancer and anti-viral therapeutic interventions.
阿尔茨海默病(AD)是一种严重的脑部神经退行性疾病,表现为痴呆、定向障碍、言语困难以及进行性认知和行为损害。AD治疗的新兴方法是抑制β-位点APP裂解酶-1(BACE1),已知它是裂解β-淀粉样前体蛋白(APP)的两种天冬氨酸蛋白酶之一。研究证实,高BACE1活性与含β-淀粉样蛋白的神经斑块形成能力相关,而神经斑块是AD的特征。市场上仅有少数几种获得美国食品药品监督管理局(FDA)批准的BACE1抑制剂,但它们的脱靶不良反应限制了其使用。在本文中,我们采用了基于配体和基于靶点的药物设计方法。定量构效关系(QSAR)研究涉及使用552个具有可接受统计性能(R² = 0.82,Q² = 0.81)的分子创建一个多变量遗传算法-多元线性回归(GA-MLR)模型。根据QSAR研究,活性与各种原子有很强的联系,如芳香碳、环硫、受体原子、sp²杂化氧等。随后,一个包含26467种食品化合物的数据库主要用于基于QSAR的虚拟筛选,并应用了Lipinski五规则;去除重复物、盐和金属衍生物后,得到了一个由8453个分子组成的精简数据集。计算了分子描述符,并使用一个经过充分验证的6参数版本的QSAR模型来预测这8453种食品化合物的生物活性。在此之后,将预测活性(pKi)高于7.0 M的食品化合物进一步对接至BACE1受体,从而鉴定出4-(3,4-二羟基苯基)-2-羟基-1H-菲-1-酮(PubChem编号:4468;食品编号:FDB017657)为命中分子(结合亲和力 = -8.9 kcal/mol,pKi = 7.97 nM,Ki = 10.715 M)。此外,150 ns的分子动力学模拟和分子力学广义玻恩表面面积(MMGBSA)研究有助于识别与BACE1酶相互作用中涉及的结构基序。分子对接和QSAR产生了互补且一致的结果。经过验证的分析可用于提高药物/先导候选物对BACE1的抑制效力。因此,我们的方法有望拓宽将营养保健品重新用于神经保护以及抗癌和抗病毒治疗干预的研究领域。