Computational search for putative inhibitors of MAP-tau hyperphosphorylation in Alzheimer's disease

Alzheimer's disease (AD), which has no known cure, is currently the most common neurodegenerative disease. Since the average age of the global population is constantly rising, AD is also recognized as one of the diseases with the quickest rate of growth. The loss of memory and executive functions is a hallmark of AD. This disease is characterized by aggregation of microtubule-associated protein tau and βamyloid peptides, which are components of neurofibrillary tangles (NFTs) and amyloid plaques, respectively. It has been demonstrated that one of the primary factors contributing to the development of AD is the aggregation of the microtubule-associated protein tau (MAPT), which was found to promote microtubule instability. This aggregation originates from the hyperphosphorylation of protein tau, which reduces its ability to bind to microtubules. The aim of this study is to identify potential inhibitors useful to reduce protein tau hyperphosphorylation and prevent the progression of Alzheimer’s disease. The first phase of this project involved researching the function and structure of the tau protein, with a focus on potential phosphorylation sites. Tau is phosphorylated during both healthy and pathological activities. It has been observed that protein tau has roughly 80 possible phosphorylation sites, and that over 50% of these sites are phosphorylated in the AD brain. By conducting this research, it was possible to identify the enzymes responsible to the phosphorylation of each of these sites, 17 different enzymes have been identified. After that it was possible to begin a thorough investigation into potential inhibitors useful to lowering the activity of these enzymes. As a result, each enzyme's possible inhibitors were found. The metabolites of each of these inhibitors have been identified by using the comprehensive computational tool Biotransformer. The focus of the study's final phase was to determine whether these inhibitors and their metabolites could inhibit the previously identified enzymes directly into the brain, due to this crucial quality, understanding how phosphorylation enzymes are expressed in various tissues and organs was essential for selecting the best inhibitors that would effectively produce the desired effect. The ability of each compound to cross the blood brain barrier was evaluated using ADMET software by analyzing the values of the BBB Filter and the LogBB, with a focus on any potential violations of Lipinski’s rule of 5. The best inhibitor among those identified for each enzyme under test could be selected using the values of the elements described above. The results of this study will enable further exploration of the inhibitors' potential to prevent the hyperphosphorylation of tau protein from setting off the chain of events that results in the onset of Alzheimer's disease.