Department of Biochemistry, Centre for Research and Development, PRIST University, Vallam, Thanjavur, Tamil Nadu, India.
Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Curr Pharm Des. 2021;27(20):2425-2434. doi: 10.2174/1381612827666210226123240.
With the burgeoning worldwide aging population, the incidence of Alzheimer's disease (AD) and its associated disorders is continuously rising. To appraise other relevant drug targets that could lead to potent enzyme targeting, 13 previously predicted ligands (shown favorable binding with AChE (acetylcholinesterase) and GSK-3 (glycogen synthase kinase) were screened for targeting 3 different enzymes, namely butyrylcholinesterase (BChE), monoamine oxidase A (MAO-A), and monoamine oxidase B (MAO-B) to possibly meet the unmet medical need of better AD treatment.
The study utilized in silico screening of 13 ligands against BChE, MAO-A and MAOB using PyRx-Python prescription 0.8. The visualization of the active interaction of studied compounds with targeted proteins was performed by Discovery Studio 2020 (BIOVIA).
The computational screening of studied ligands revealed the docking energies in the range of -2.4 to -11.3 kcal/mol for all the studied enzymes. Among the 13 ligands, 8 ligands (55E, 6Z2, 6Z5, BRW, F1B, GVP, IQ6, and X37) showed the binding energies of ≤ -8.0 kcal/mol towards BChE, MAO-A and MAO-B. The ligand 6Z5 was found to be the most potent inhibitor of BChE and MAO-B, with a binding energy of -9.7 and -10.4 kcal mol, respectively. Molecular dynamics simulation of BChE-6Z5 and MAO-B-6Z5 complex confirmed the formation of a stable complex.
Our computational screening, molecular docking, and molecular dynamics simulation studies revealed that the above-mentioned enzymes targeted ligands might expedite the future design of potent anti-AD drugs generated on this chemical scaffold.
随着全球老龄化人口的不断增加，阿尔茨海默病（AD）及其相关疾病的发病率持续上升。为了评估其他可能导致有效酶靶向的相关药物靶点，对 13 种先前预测的配体（与乙酰胆碱酯酶（AChE）和糖原合酶激酶（GSK-3）具有良好的结合）进行了筛选，以针对 3 种不同的酶，即丁酰胆碱酯酶（BChE）、单胺氧化酶 A（MAO-A）和单胺氧化酶 B（MAO-B），以可能满足更好治疗 AD 的未满足的医疗需求。
本研究利用 PyRx-Python 处方 0.8 对 13 种针对 BChE、MAO-A 和 MAOB 的配体进行了计算机筛选。通过 Discovery Studio 2020（BIOVIA）对研究化合物与靶蛋白的活性相互作用进行了可视化。
研究配体的计算筛选显示，所有研究酶的对接能范围为-2.4 至-11.3 kcal/mol。在 13 种配体中，有 8 种配体（55E、6Z2、6Z5、BRW、F1B、GVP、IQ6 和 X37）对 BChE、MAO-A 和 MAO-B 的结合能均≤-8.0 kcal/mol。发现配体 6Z5 是 BChE 和 MAO-B 的最有效抑制剂，其结合能分别为-9.7 和-10.4 kcal mol。BChE-6Z5 和 MAO-B-6Z5 复合物的分子动力学模拟证实了稳定复合物的形成。
我们的计算筛选、分子对接和分子动力学模拟研究表明，上述针对酶的配体可能加速基于该化学支架的有效抗 AD 药物的未来设计。
