Abstract
The translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor (PBR), is found in the outer mitochondrial membrane of several eukaryotic organisms, including humans. Its protein expression in Neuroglia cells is upregulated under certain neurological conditions such as brain inflammation (BI), Parkinson's and Alzheimer's diseases. However, the exact function of TSPO has yet to be found. This observed upregulation of makes TSPO a target of interest as inhibiting TSPO with selective ligands may produce therapeutic effect for neurodegenerative diseases. It has been shown that increasing the therapeutic window to treat BI requires increasing the residence time (RT) of a TSPO-ligand complex, thereby increasing the pharmacological activity of the ligand. To develop new potential ligands, it is crucial to understand the unbinding kinetics of existing ligands. Molecular dynamics (MD) is suited to provide this information, but is limited if the size of he unbinding energy barriers between the bound and unbound states are too great to overcome in classical MD simulations.. It has been previously shown that weighted ensemble algorithms can successfully overcome such barriers. Using a variant of the weighted ensemble method, Reweighting of Ensemble by Variance Optimization (REVO) we simulate the unbinding kinetics of PK11195, a molecule selective to TSPO with high affinity used as a biomarker in positron emission tomography (PET) scans We ran several independent simulations to determine the statistical likelihood of each state in the free energy landscape. We have determined possible pathways for PK11195 to unbind from TSPO, including routes involving exit through the membrane. We visualize and analyze these unbinding pathways by constructing a conformational space network (CSN) demonstrating the spatial relationship and conformation probability of these states. These results allow us to design novel ligands with longer RTs, improving their potential for clinical use.
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