期刊
JOURNAL OF MEDICINAL CHEMISTRY
卷 61, 期 13, 页码 5719-5732出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jmedchem.8b00653
关键词
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资金
- Excellence Initiative of Aix-Marseille University A*MIDEX, a French Investissements d'Avenir program
- Canceropole PACA
- Institut National du Cancer
- Region Provence-Alpes-Cote d'Azur [2018-03]
- Fondation ARC [PJA20171206125]
- ANR [ANR-15-CE18-0023]
- A*MIDEX
- Metchnikov Ph.D. fellowship from the French government
- Fondation ARC pour la Recherche sur le Cancer
- Fondation pour la Recherche Medicale (FRM)
- FRISBI [ANR-10-INSB-05-01]
- Agence Nationale de la Recherche (ANR) [ANR-15-CE18-0023] Funding Source: Agence Nationale de la Recherche (ANR)
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 or bromodomain inhibitors as a test case, leaning to the validation or several compounds with improved affinity by several orders of magnitude.
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