Alzheimers disease (AD) is highly complex. While several pathologies characterize this disease, amyloid plaques, composed of the β-amyloid peptide, are hallmark neuropathological lesions in Alzheimers disease brain. Indeed, a wealth of evidence suggests that β-amyloid is central to the pathophysiology of AD and is likely to play an early role in this intractable neurodegenerative disorder. The BACE-1 enzyme is essential for the generation of β-amyloid. BACE-1 knockout mice do not produce β-amyloid and are free from Alzheimers associated pathologies, including neuronal loss and certain memory deficits. The fact that BACE-1 initiates the formation of β-amyloid, and the observation that BACE-1 levels are elevated in this disease provide direct and compelling reasons to develop therapies directed at BACE-1 inhibition, thus reducing β-amyloid and its associated toxicities. In this sense, quantitative structure-activity relationships (QSAR) could play an important role in studying these β-secretase inhibitors. QSAR models are necessary in order to guide the β-secretase synthesis. This work is aimed at reviewing different design and synthesis and computational studies for a very large and heterogeneous series of β-secretase inhibitors. First, we review design, synthesis, and Biological assay of β-secretase inhibitors. Next, we review 2D QSAR, 3D QSAR, CoMFA, CoMSIA and Docking with different compounds to find out the structural requirements. Next, we review QSAR studies using the method of Linear Discriminant Analysis (LDA) in order to understand the essential structural requirement for receptor binding for β- secretase inhibitors.
Keywords: QSAR, CoMSIA, COMFA, topological indices, β-secretase inhibitors, Alzheimer's disease (AD), amyloid plaques, LDA, ADMET, metabolomics
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