Background: Parkinson’s disease is characterized by decreased level of dopaminergic neurotransmitters and this decrease is due to the degradation of dopamine by protein Monoamine Oxidase B (MAO-B). In order to treat Parkinson’s disease, MAO-B should be inhibited.

Objective: To find out the novel phytochemicals from plant Ocimum basilicum that can inhibit MAO-B by using the in silico methods.

Methods: The data of chemical constituents from plant Ocimum basilicum was collected and inhibitory activity of these phytochemicals was then predicted by using the Structure-Based (SB) and Ligand-Based Virtual Screening (LBVS) methods. Molecular docking, one of the common Structure-Based Virtual Screening method, has been used during this search. Traditionally, molecular docking is used to predict the orientation and binding affinity of the ligand within the active site of the protein. Molegro Virtual Docker (MVD) software has been used for this purpose. On the other hand, Random Forest Model, one of the LBVS method, has also been used to predict the activity of these chemical constituents of Ocimum basilicum against the MAO-B.

Results: During the docking studies, all the 108 compounds found in Ocimum basilicum were docked within the active site of MAO-B (PDB code: 4A79) out of which, 57 compounds successfully formed the hydrogen bond with tyr 435, a crucial amino acid for the biological activity of the enzyme. Rutin (-182.976 Kcal/mol), Luteolin (-163.171 Kcal/mol), Eriodictyol-7-O-glucoside (- 160.13 Kcal/mol), Rosmarinic acid (-133.484 Kcal/mol) and Isoquercitrin (-131.493 Kcal/mol) are among the top hits with the highest MolDock score along with hydrogen interaction with tyr 435. Using the RF model, ten compounds out of 108 chemical constituent of Ocimum basilicum were predicted to be active, Apigenin (1.0), Eriodictyol (1.0), Orientin (0.876), Kaempferol (0.8536), Luteolin (0.813953) and Rosmarinic-Acid (0.7738095) are predicted to be most active with the highest RF score.

Conclusion: The comparison of the two screening methods show that the ten compounds that were predicted to be active by the RF model, are also found in top hits of docking studies with the highest score. The top hits obtained during this study are predicted to be the inhibitor of MAO-B, thus, could be used further for the development of drugs for the treatment of Parkinson’s disease (PD).

背景：帕金森氏病的特点是多巴胺能神经递质水平降低，而这种下降是由于蛋白单胺氧化酶B（MAO-B）降解了多巴胺。为了治疗帕金森氏病，应抑制MAO-B。

目的：采用计算机模拟技术，从植物罗勒属植物中发现能够抑制MAO-B的新型植物化学物质。

方法：收集植物罗勒属植物的化学成分数据，然后使用基于结构的（SB）和基于配体的虚拟筛选（LBVS）方法预测这些植物化学物质的抑制活性。分子对接是一种常见的基于结构的虚拟筛选方法，已在此搜索过程中使用。传统上，分子对接用于预测蛋白质活性位点内配体的方向和结合亲和力。Molegro虚拟Docker（MVD）软件已用于此目的。另一方面，LBVS方法之一的随机森林模型也已用于预测罗勒叶这些化学成分对MAO-B的活性。

结果：在对接研究中，罗勒叶中发现的所有108种化合物都被对接在MAO-B的活性位点内（PDB代码：4A79），其中57种化合物成功地与tyr 435形成了氢键，tyr 435是一种关键氨基酸酶的生物活性。芦丁（-182.976 Kcal / mol），木犀草素（-163.171 Kcal / mol），松香醇-7-O-葡萄糖苷（-160.13 Kcal / mol），迷迭香酸（-133.484 Kcal / mol）和异槲皮苷（-131.493 Kcal / mol） ）是在MolDock分数最高的命中以及与tyr 435发生氢相互作用的热门命中。使用RF模型，可以预测罗汉葵（Ocimum basilicum）108种化学成分中有10种化合物具有活性，芹菜素（1.0），E香酚（1.0）， Orientin（0.876），Kaempferol（0.8536），Luteolin（0.813953）和迷迭香酸（0。

结论：两种筛选方法的比较表明，RF模型预测的十种化合物在对接研究的最高命中也得分最高。预计在这项研究中获得的最高成功是MAO-B的抑制剂，因此可以进一步用于开发治疗帕金森氏病（PD）的药物。