Identification of Novel Phyto-chemicals from Ocimum Bacillicum for the Treatment of Parkinson’s Disease using In-silico Approach

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Author(s): Nageen Mubashir, Rida Fatima, Sadaf Naeem*.

Journal Name: Current Computer-Aided Drug Design

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Background: Parkinson’s disease is characterized by decreased level of dopaminergic neurotransmitters and this decrease is due to the degradation of dopamine by protein human 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 bacillicum that can inhibit MAO-B by using the in-silico methods.

Methods: The data of chemical constituents from plant Ocimum bacillicum 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 bacillicum against the MAO-B.

Results: During the docking studies, all the 108 compounds found in Ocimum bacillicum were docked within the active site of MAO-B (PDB code: 4A79) out of which, 57 compounds successfully formed the hydrogen bond with the tyr 435, a crucial amino acid for the biological activity of the enzyme. Rutin (-182.976 Kcal/mol), Luteolin (-163.171 Kcal/mol), Eriodictylol-7-O-glucoside (-160.13 Kcal/mol), Rosmaranic 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 bacillicum 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 shows that the ten compounds that were predicted to be active by the RF model, is 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).

Keywords: Parkinson’s disease, Monoamine Oxidase, Molecular Docking, Random Forest Model

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Article Details

(E-pub Ahead of Print)
DOI: 10.2174/1573409915666190503113617
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