Computational Modeling Studies of the LRRK2 Protein in the Mechanism of Parkinson’s Disease

Hetvi Shah and Jerry A Darsey
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Jerry A Darsey: Department of Chemistry, Center for Molecular Design and Development & University of Arkansas at Little Rock, USA

Current Trends in Biomedical Engineering & Biosciences, 2017, vol. 9, issue 1, 9-14

Abstract: Parkinson’s disease is a disorder of the nervous system, affecting movement. The most common gene mutation is said to be in the Leucine-rich repeat kinase 2 (LRRK2) gene, which provides instructions to make the LRRK2 protein. The functions that the protein carries out results in abnormalities, leading to Parkinson’s disease. If a molecule binds to the active site of LRRK2 protein, it could lead to potential treatment. To create the potential drug molecule for treatment of Parkinson’s disease, the IC50 value is an essential experimental parameter to know, because it determines the effectiveness and strength of binding to the protein. Therefore, this research determined whether or not there was a correlation between the IC50 value and the total energy, dipole moment, or energy gap of a molecules that are said to bind to LRRK2, with experimentally measured IC50 values. The energy gap was established by subtracting the HOMO from the LUMO. The total energy, dipole moment, and HOMO/LUMO values were found by modeling and running all molecules using the molecular modeling program, Gaussian 09. After all the values were found, combinations were made, where either IC50, 1/IC50, or log IC50 was the x-axis, and the total energy, energy gap, or dipole moments was the y-axis. A strong correlation was found between 1/IC50 and total energy, with the R2 value being 0.94. Therefore, these results support the conclusion that a strong correlation was found. This can now be used as a reference to find the IC50 value when doing further experimentation on designing new molecules in which the IC50 values have not be experimentally measured. This analysis is the first step in assisting researchers to reach potential drug molecules for treating Parkinson’s Disease.

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Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jctbeb:v:9:y:2017:i:1:p:9-14

DOI: 10.19080/CTBEB.2017.09.555754

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