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Identification of potential glutaminyl cyclase inhibitors from lead-like libraries by in silico and in vitro fragment-based screening.

Mária SzaszkóIstván HajdúBeáta FlachnerKrisztina DobiCsaba MagyarIstván SimonZsolt LőrinczZoltán KapuiTamás PázmánySándor CsehGyörgy Dormán
Published in: Molecular diversity (2017)
A glutaminyl cyclase (QC) fragment library was in silico selected by disconnection of the structure of known QC inhibitors and by lead-like 2D virtual screening of the same set. The resulting fragment library (204 compounds) was acquired from commercial suppliers and pre-screened by differential scanning fluorimetry followed by functional in vitro assays. In this way, 10 fragment hits were identified ([Formula: see text]5 % hit rate, best inhibitory activity: 16 [Formula: see text]). The in vitro hits were then docked to the active site of QC, and the best scoring compounds were analyzed for binding interactions. Two fragments bound to different regions in a complementary manner, and thus, linking those fragments offered a rational strategy to generate novel QC inhibitors. Based on the structure of the virtual linked fragment, a 77-membered QC target focused library was selected from vendor databases and docked to the active site of QC. A PubChem search confirmed that the best scoring analogues are novel, potential QC inhibitors.
Keyphrases
  • molecular docking
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  • artificial intelligence
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  • electron microscopy