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).
Fusing Docking Scoring Functions Improves the Virtual Screening Performance for Discovering Parkinson's Disease Dual Target Ligands
