Alzheimer's disease (AD) is the most prevalent form of dementia, and current indications show that twenty-nine million people live with AD worldwide, a figure expected rise exponentially over the coming decades. AD is characterize with several pathologies this disease, amyloid plaques, composed of the β-amyloid peptide and γ-amyloid peptide are hallmark neuropathological lesions in Alzheimer's 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. For this reason, we developed a new QSAR (QSAR) model to discover new drugs. A public databases ChEMBL contain Big Data sets of inhibitors of β-secretase. We revised QSAR studies using method of Artificial Neural Network (ANN) in order to understand the essential structural requirement for binding with receptor for β-secretase inhibitors.
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Two QSAR Paradigms- Congenericity Principle versus Diversity Begets Diversity Principle- analyzed using computed mathematical chemodescriptors of homogeneous and diverse sets of chemical mutagensNext Article in congress
New theoretical model for the study of new β-secretase inhibitors
Published: 04 December 2015 by MDPI in MOL2NET'15, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 1st ed. congress USEDAT-01: USA-Europe Data Analysis Training Congress, Cambridge, UK-Bilbao, Spain-Miami, USA, 2015
Keywords: QSAR; β-secretase inhibitors; Alzheimer's disease (AD)