Discovery of BACE-1 inhibitors using an integrated computational and experimental approach

There are numerous complementary approaches to facilitate the identification of novel inhibitors for biological targets, including high throughput screening and fragment-based drug discovery. Computational tools are often employed to predict binding pose and affinity of the new inhibitors. In this thesis an integrated computational and experimental approach to identify novel inhibitors is described. The approach involves the design of a virtual library of likely synthetically accessible lead-like molecules, followed by virtual high throughput screening (vHTS) against target protein. To exemplify the approach, BACE-1 was selected as an example target protein. BACE-1 is responsible for the formation of amyloidal plaque in brains affected by Alzheimer’s disease and therefore is a potential target for the treatment of the disease.
A virtual library of lead-like molecules was generated based on diversity-oriented synthesis methods established in our laboratory. The library underwent virtual high throughput screening (vHTS) against BACE-1 by using eHiTS and two families of putative inhibitors were identified with high predicted ligand efficiency (cLE). The in silico approach employed to identify novel putative BACE-1 inhibitors is schematically represented as follows.

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A focused library based on the selected putative inhibitors was designed and synthesised, and biological activity was assessed via a fluorimetric assay. Structure-activity relationship (SAR) studies were conducted to rationalise the activity of the inhibitors and to confirm the validity of the integrated approach in identifying new inhibitors for biological targets. A novel series of BACE-1 inhibitors was identified and is herein described.