Computer-Aided Drug Design Applied to Beta and Gamma Secretase Inhibitors-Perspectives for New Alzheimer Disease Therapy

Abstract

Alzheimers disease (AD) is characterized by the presence of extracellular amyloid plaques, containing the extracellular amorphous deposits of beta-amyloid protein and intracellular neurofibrillary tangles, comprising filaments of phosphorylated form of a microtubule-associated protein Tau, localized in the brain. It is considered that the major constituent of amyloid plaques, beta-amyloid peptide (Aβ), induces AD neuropathology. AD enzymatic pathway comprises several events: (i) beta-secretase cleaves amyloid precursor protein (APP) and releases a soluble fragment, beta-APPs, and (ii) gamma-secretase cleaves the C-terminal membrane bound C99 peptide within the transmembrane domain, thus generating two major amino acid isoforms of beta-amyloid: Aβ40 and Aβ42. This review is focused on the recent advances in the field of computational chemistry (molecular docking, 3D-QSAR (CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis)), molecular dynamics and rational drug design) applied to inhibitions of beta and gamma secretases. Computational chemistry studies have been performed for different inhibitors of beta and gamma secretases (e.g. benzodiazepine, urethane and tetrapeptide derivatives) resulting in their predicted biological activities and free energies. Keywords: Alzheimer's disease, gamma and beta secretases inhibition, computational chemistry