20 June 2016

19F-NMR-guided fragment linking on BACE1

Fragment growing has been the dominant strategy of most of the recent posts involving lead optimization, consistent with our poll results. However, fragment linking can be powerful too, as illustrated by the recent approval of venetoclax, which was derived from fragment linking. A recent paper in J. Med. Chem. by Brad Jordan and colleagues at Amgen provides another nice case study.

Amgen researchers had previously used fragment growing to discover inhibitors of BACE1, an Alzheimer’s target which has been heavily tackled by fragments. However, the most potent molecules in the series also inhibited the related aspartic protease cathepsin D (CatD), which could cause serious side effects. The researchers sought to gain selectivity by building inhibitors to occupy the so-called S3subpocket of BACE1. To do so, they used 19F-NMR to find fragments that would bind to BACE1 in the presence of a “blocking compound” that filled most of the active site but not the S3subpocket. This led to the discovery of seven fragments, the most potent being compound 3. Interestingly, this fragment only bound in the presence of the blocking compound as assessed both by NMR and SPR. Also, it could be competed by a compound that binds in the S3subocket.

Having thus identified a fragment that bound in the presence of one of their inhibitors, the researchers used interligand NOE (ILOE) to determine how the two compounds bind relative to one another. This supported the idea that compound 3 binds in the S3subpocket, and also suggested how the fragment could be linked onto the existing lead series, exemplified by compound 5. Just four compounds were designed and synthesized, and all of them were more potent than either of the starting points, with compound 9 being the best. More importantly, this compound also proved to be ~2000-fold selective for BACE1 over CatD in enzymatic and cell-based assays.

Despite the excellent (high picomolar) affinity of compound 9 for BACE1, this is actually about 25-fold worse than would be predicted by a simplistic additivity of binding energies – a not uncommon occurrence when linking molecules. Still, with its combined used of multiple NMR techniques and structure-based design to solve a specificity challenge, this paper is worth perusing.

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