After Alzheimer's disease, Parkinson's disease (PD) is the second most prevalent neurological illness. Clinically, it is defined by parkinsonism, which includes stiffness, bradykinesia, resting tremor, and postural instability. Pathologically, it is characterized by the loss of substantia nigra neurons. Monoamine oxidases (MAO-A and MAO-B) are enzymes responsible for metabolizing neurotransmitters such as dopamine (DA) and adrenaline. Selective MAO-A or MAO-B inhibitors have been the focus of recent attempts to create MAO inhibitors. In addition, Parkinson's disease can be effectively treated with MAO-B inhibitors.
The objective is to elucidate the several types of interactions between enzymes and ligands and assess the stability of the resulting complexes.
Various molecular modeling methods are used to study the inhibition of the enzyme MAO-B (PDB:4a79) involved in PD, including molecular docking, molecular dynamics, MOE software, and ADME prediction.
Based on the findings, compound L30 and compound L38, the top contenders identified by molecular docking/dynamic simulations and with low energy scores, had low IC50 values (0.110 and 0.305 µM, respectively).
The combination of the two outcomes from the earlier techniques demonstrates that the compounds L30 and L38 were chosen as the most effective MAO-B inhibitors and that they also satisfy the Lipinski, Veber, and Egan rules. They are also able to traverse the BBB. Furthermore, they may be utilized to create novel pharmaceutical medicines to treat individuals with PD.
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Studying the inhibitory activity of novel series compounds for Parkinson's disease using a molecular docking method
Published:
12 April 2024
by MDPI
in The 3rd International Electronic Conference on Biomolecules
session Bioinformatics and Computational Biology
Abstract:
Keywords: Parkinson's disease, Molecular Docking, Molecular Dynamic, ADME, Interaction.