| dc.description.abstract | Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD) are neurodegenerative diseases which may be caused by neuronal apoptosis and there are currently no treatments to delay the progression of these diseases. Finding a cure or delaying the progression of these diseases, will improve the quality of life of the patients and relieve the burden on the caregivers and loved ones of the patients. Many enzymes are involved in the apoptotic processes that contribute to neurodegenerative diseases. These enzymes include CDK5/p25 (Cyclin dependent kinase 5 in complex with activator protein p25), calpain I, caspase 3 and GSK313 (Glycogen synthase kinase 313). Inhibition of these enzymes will have the potential to counteract the neurodegeneration caused by various apoptotic processes. In this study, computational pharmacophore hypotheses for CDK5/p25, calpain I, caspase 3 and GSK313 were formulated to predict the geometry of the chemical features necessary to exhibit inhibitory activity against these enzymes. The generated hypotheses were validated using published structures with known activity and an in-house library of compounds was screened to determine which compounds comply with the hypotheses for the respective enzymes. Docking studies were subsequently performed using the in-house library to determine which compounds have the ability to fit into the respective enzyme cavities, thus having potential as inhibitors for the specific enzymes. Using a combination of docking results and hypothesis compliance, the compounds with the most promising combined results were selected for biological screening in enzyme assays. The 'pharmacophore hypothesis in combination with docking studies' model had the best predictive capabilities for calpain I and GSK313 (60% and 85% respectively) and these enzymes were therefore selected for the biological assays to serve as in vitro proof of concept. The most potent inhibitor identified for calpain I, which was a hypothesis hit as well as having a better dock score than the co-crystallised ligand, had an IC50 value of 95.42 uM. The most potent inhibitor identified for GSK3B, which was a hypothesis hit as well as having a better dock score than that of the co-crystallised ligand, had an IC50 value of 0.6819 uM. Molecular dynamics were subsequently performed on selected compounds from the biological assays to determine binding modes and active conformations. Critical interactions necessary for enzyme inhibition was identified for both enzymes from the molecular modelling studies. In this study, hypothesis generation, combined with docking studies, were found to be valuable to identify scaffolds and can be effectively applied during drug design of kinase and related enzyme inhibitors. The identified scaffolds could be further optimised as drug leads to design potent inhibitors during future studies. | en_US |
