RESUMEN
Over the past few decades, hit identification has been greatly facilitated by advances in high-throughput and fragment-based screenings. One major hurdle remaining in drug discovery is process automation of hit-to-lead (H2L) optimization. Here, we report a time- and cost-efficient integrated strategy for H2L optimization as well as a partially automated design of potent chemical probes consisting of a focused-chemical-library design and virtual screening coupled with robotic diversity-oriented de novo synthesis and automated in vitro evaluation. The virtual library is generated by combining an activated fragment, corresponding to the substructure binding to the target, with a collection of functionalized building blocks using in silico encoded chemical reactions carefully chosen from a list of one-step organic transformations relevant in medicinal chemistry. The proof of concept was demonstrated using the optimization of bromodomain inhibitors as a test case, leading to the validation of several compounds with improved affinity by several orders of magnitude.
Asunto(s)
Descubrimiento de Drogas/métodos , Técnicas de Química Sintética , Reproducibilidad de los Resultados , Bibliotecas de Moléculas Pequeñas/química , Bibliotecas de Moléculas Pequeñas/farmacología , Factores de TiempoRESUMEN
A midthroughput screening follow-up program targeting the first bromodomain of the human BRD4 protein, BRD4(BD1), identified an acetylated-mimic xanthine derivative inhibitor. This compound binds with an affinity in the low micromolar range yet exerts suitable unexpected selectivity in vitro against the other members of the bromodomain and extra-terminal domain (BET) family. A structure-based program pinpointed a role of the ZA loop, paving the way for the development of potent and selective BET-BRDi probes.