Structure-based virtual screening of natural products as potential inhibitors of proteins associated with Alzheimer's disease - Suarez, Angelica Faith L (University of the Philippines in the Visayas, 2019)
Alzheimer's disease (AD), classified as the most common type of dementia, affects around 44.4 million people worldwide. Several reports revealed that the accumulation of amyloid-B plaques in the brain, which are cleaved by secretase enzymes, affects the synaptic residence time of neurotransmitters leading to the degeneration of neurons. However, after successive clinical trials and drug development researches for AD, it has been reported that drugs and treatments are failing due to declining efficacy and unforeseen toxicity. Hence, the integration of structure-based virtual screening and ADMET (adsortion, distribution, metabolism, excretion, and toxicity) evaluation of compounds as putative ihhibitors of proteins associated with AD was employed in this study to provide a comprehensive profile and assessment of drug candidates. We screened compounds with high affinity to the known binding site of secretase and acetylcholinesterase using molecular docking tools. The drug-likeness of the candidates with high docking scores were evaluated using its ADMET properties. Molecular networking using Tanimoto similarity was performed on the drug candidates to obtain its correlation and clustering with respect to its inhibitory activities. Our findings shed light o the design, combinational treatment as well as repurposing efforts in drug discovery and development against Alzheimer's disease.