Journal of Medicinal Chemistry · 2018 · 70 citations · 25 references
Drug TargetHit IdentificationMolecular BiologyLead IdentificationChemistryChemical BiologyH2l OptimizationMedicinal ChemistrySmall Molecule LibraryMaterials ScienceVirtual ScreeningBiochemistryDe Novo Drug DesignDiversity-oriented SynthesisDiversity-oriented-target-focused-synthesis ApproachCatalysisSynthesis MethodLead OptimizationNatural SciencesRational Drug DesignSynthetic BiologyMedicineDrug DiscoveryHigh-throughput Screening
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.
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Features and development of <i>Coot</i>
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