Hiralal Mazumdar Memorial College for Women, West Bengal State University, Kolkata, West Bengal, India.
Department of Basic Medical Science, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.
PLoS One. 2024 Jul 25;19(7):e0301179. doi: 10.1371/journal.pone.0301179. eCollection 2024.
Alzheimer's Disease (AD) is the prevailing type of neurodegenerative illness, characterised by the accumulation of amyloid beta plaques. The symptoms associated with AD are memory loss, emotional variability, and a decline in cognitive functioning. To date, the pharmaceuticals currently accessible in the marketplace are limited to symptom management. According to several research, antidepressants have demonstrated potential efficacy in the management of AD. In this particular investigation, a total of 24 anti-depressant medications were selected as ligands, while the Microtubule Affinity Receptor Kinase 4 (MARK4) protein was chosen as the focal point of our study. The selection of MARK4 was based on its known involvement in the advancement of AD and other types of malignancies, rendering it a highly prospective target for therapeutic interventions. The initial step involved doing ADMET analysis, which was subsequently followed by molecular docking of 24 drugs. This was succeeded by molecular dynamics simulation and molecular mechanics generalised Born surface area (MMGBSA) calculations. Upon conducting molecular docking experiments, it has been determined that the binding affinities observed fall within the range of -5.5 kcal/mol to -9.0 kcal/mol. In this study, we selected six anti-depressant compounds (CID ID - 4184, 2771, 4205, 5533, 4543, and 2160) based on their binding affinities, which were determined to be -9.0, -8.7, -8.4, -8.3, -8.2, and -8.2, respectively. Molecular dynamics simulations were conducted for all six drugs, with donepezil serving as the control drug. Various analyses were performed, including basic analysis and post-trajectory analysis such as free energy landscape (FEL), polarizable continuum model (PCM), and MMGBSA calculations. Based on the findings from molecular dynamics simulations and the MMGBSA analysis, it can be inferred that citalopram and mirtazapine exhibit considerable potential as anti-depressant agents. Consequently, these compounds warrant further investigation through in vitro and in vivo investigations in the context of treating AD.
阿尔茨海默病(AD)是最常见的神经退行性疾病,其特征是淀粉样β斑块的积累。与 AD 相关的症状包括记忆力减退、情绪变化和认知功能下降。迄今为止,市场上可获得的药物仅限于症状管理。根据多项研究,抗抑郁药已被证明在 AD 的治疗中具有潜在疗效。在这项特殊的研究中,总共选择了 24 种抗抑郁药作为配体,而微管亲和受体激酶 4(MARK4)蛋白被选为我们研究的焦点。选择 MARK4 是基于其已知参与 AD 和其他类型恶性肿瘤的进展,使其成为治疗干预的极具前景的靶点。第一步是进行 ADMET 分析,随后对 24 种药物进行分子对接。接着进行分子动力学模拟和分子力学广义 Born 表面积(MMGBSA)计算。在进行分子对接实验后,确定观察到的结合亲和力在-5.5 kcal/mol 到-9.0 kcal/mol 范围内。在这项研究中,我们根据结合亲和力选择了六种抗抑郁化合物(CID ID - 4184、2771、4205、5533、4543 和 2160),它们的结合亲和力分别为-9.0、-8.7、-8.4、-8.3、-8.2 和-8.2。对所有六种药物进行了分子动力学模拟,以多奈哌齐作为对照药物。进行了各种分析,包括基本分析和后轨迹分析,如自由能景观(FEL)、极化连续体模型(PCM)和 MMGBSA 计算。基于分子动力学模拟和 MMGBSA 分析的结果,可以推断出西酞普兰和米氮平具有作为抗抑郁药的巨大潜力。因此,这些化合物值得通过体外和体内研究进一步研究,以治疗 AD。