Exploring 2D-QSAR for prediction of beta-secretase 1 (BACE1) inhibitory activity against Alzheimer's disease. Issue 2 (1st February 2020)

• Record Type: Journal Article
• Authors: Kumar, V.; Ojha, P.K.; Saha, A.; Roy, K.
• Is Part Of: SAR and QSAR in environmental research. Volume 31:Issue 2(2020)
• Page Start: 87
• Page End: 133
• Publication Date: 2020-02-01
• Subjects: BACE1 -- Alzheimer's disease -- QSAR -- validation -- OECD -- Aβ -- DModX; Structure-activity relationships (Biochemistry) -- Periodicals; QSAR (Biochemistry) -- Periodicals; 572.4
• DOI: 10.1080/1062936X.2019.1695226
• Languages: English
• ISSNs: 1062-936X

Abstract

ABSTRACT: We have developed a robust quantitative structure–activity relationship (QSAR) model employing a dataset of 98 heterocycle compounds to identify structural features responsible for BACE1 (beta-secretase 1) enzyme inhibition. We have used only 2D descriptors for model development purpose thus avoiding the conformational complications arising due to 3D geometry considerations. Following the strict Organization for Economic Co-operation and Development (OECD) guidelines, we have developed models using stepwise regression analysis followed by the best subset selection, while the final model was developed by partial least squares regression technique. The model was validated using various internationally accepted stringent validation parameters. From the insights obtained from the developed model, we have concluded that heteroatoms (nitrogen, oxygen, etc.) present within to an aromatic nucleus and the structural features such as hydrophobic, ring aromatic and hydrogen bond acceptor/donor are responsible for the enhancement of the BACE1 enzyme inhibitory activity. Moreover, we have performed the pharmacophore modelling to unveil the structural requirements for the inhibitory activity against the BACE1 enzyme. Furthermore, molecular docking studies were carried out to understand the molecular interactions involved in binding, and the results are then correlated with the requisite structural features obtained from the QSAR and pharmacophore models.