Affiliation:
1. University of Ibadan College of Medicine
2. Adekunle Ajasin University
3. Usmanu Danfodiyo University Faculty of Science
4. Nigerian Prisons Service
Abstract
Abstract
Background
Although there is presently no cure for Parkinson's disease (PD), the available therapies are only able to lessen symptoms and preserve the quality of life. Around 10 million people globally had PD as of 2020. The widely used standard drug has recently been revealed to have several negative effects. Additionally, there is a dearth of innovative compounds entering the market as a result of subpar ADMET characteristics. Drug repurposing provides a chance to reenergize the sluggish drug discovery process by identifying new applications for already-approved medications. As this strategy offers a practical way to speed up the process of developing alternative medications for PD. This study used a computer-aided technique to select therapeutic agent(s) from FDA-approved neuropsychiatric/psychotic drugs that can be adopted in the treatment of Parkinson's disease.
Method
In the current work, a computational approach via molecular docking, density functional theory (DFT), and pharmacokinetics were used to identify possible (anti)neuropsychiatric/psychotic medications for the treatment of PD. By using molecular docking, about eight (anti)neuropsychiatric/psychotic medications were tested against PARKIN, a key protein in PD
Result
Based on the docking score, the best ligand in the trial was determined. The top hits were compared to the reference ligand levodopa (L-DOPA). A large proportion of the drugs displayed binding affinity that was relatively higher than L-DOPA. Also, DFT analysis confirms the ligand-receptor interactions and the molecular charges transfer. All the compounds were found to obey Lipinski's rule with acceptable pharmacokinetic properties.
Conclusion
The current study has revealed the effectiveness of antineuropsychiatric/antipsychotic drugs against PARKIN in the treatment of PD and lumateperone was revealed to be the most promising candidate interacting with PARKIN.
Publisher
Research Square Platform LLC
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