Computational Modeling of Gamma-Secretase Inhibitors as Anti-Alzheimer Agents

Protocol
First Online:
Part of the Neuromethods book series (NM, volume 132)

Abstract

γ-Secretase (gamma secretase) is a complex unusual aspartyl protease, responsible for the production of amyloid-β peptides (Aβ) involved in Alzheimer’s disease (AD). Inhibition of gamma secretase (GS) is an attractive therapeutic strategy to slow down the pathological progression of AD. For a long time, GS-targeted structure-based drug designing remained unrealistic without the 3D structural knowledge of GS. Hence, to meet the prevailing urgent need for AD drugs, several groups individually tried to develop GS inhibitors, with the aid of computational drug designing methods. This chapter mainly provides with a detailed discussion on a QSAR-guided fragment-based virtual screening method for GS inhibitor design and identification. In this study, we took advantage of the wealth of available known small molecular GS inhibitors and applied in this drug designing program. Here, the non-transition state small molecular GS inhibitors with corresponding affinity values were used to develop 2D- and 3D-QSAR models investigating alternative site-binding GS inhibitors. HipHop pharmacophore-based alignment-dependent (CoMFA and CoMSIA) and GRIND-based alignment-independent 3D-QSAR models were developed to elucidate the potential 3D features involved in GS inhibition. Consensus of QSAR results from this study underscores the reliability and accuracy of the results and provides a rationale for the design of novel potent GS inhibitors that can have AD therapeutic application.

Key words

Gamma secretase Bioisosteric replacement 3D-QSAR CoMFA GRIND Inverse QSAR 
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Copyright information

© Springer Science+Business Media LLC 2018

Authors and Affiliations

  1. 1.Centre of Excellence in Bioinformatics, School of Biotechnology, Madurai Kamaraj UniversityMaduraiIndia
  2. 2.Structural Biology and Bioinformatics Division, CSIR-Indian Institute of Chemical BiologyKolkataIndia

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