Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Department of Systems Neuropharmacology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Nat Chem Biol. 2018 Mar;14(3):291-298. doi: 10.1038/nchembio.2556. Epub 2018 Jan 22.
Synthetic tailoring of approved drugs for new indications is often difficult, as the most appropriate targets may not be readily apparent, and therefore few roadmaps exist to guide chemistry. Here, we report a multidisciplinary approach for accessing novel target and chemical space starting from an FDA-approved kinase inhibitor. By combining chemical and genetic modifier screening with computational modeling, we identify distinct kinases that strongly enhance ('pro-targets') or limit ('anti-targets') whole-animal activity of the clinical kinase inhibitor sorafenib in a Drosophila medullary thyroid carcinoma (MTC) model. We demonstrate that RAF-the original intended sorafenib target-and MKNK kinases function as pharmacological liabilities because of inhibitor-induced transactivation and negative feedback, respectively. Through progressive synthetic refinement, we report a new class of 'tumor calibrated inhibitors' with unique polypharmacology and strongly improved therapeutic index in fly and human MTC xenograft models. This platform provides a rational approach to creating new high-efficacy and low-toxicity drugs.
将已批准的药物进行新适应症的人工合成改造通常很困难,因为最合适的靶点可能不太明显,因此几乎没有指导化学合成的路线图。在这里,我们报告了一种从 FDA 批准的激酶抑制剂入手,探索新靶点和化学空间的多学科方法。通过将化学和遗传修饰筛选与计算建模相结合,我们确定了不同的激酶,这些激酶在果蝇髓样甲状腺癌(MTC)模型中强烈增强(“前靶点”)或限制(“反靶点”)临床激酶抑制剂索拉非尼的整体动物活性。我们证明 RAF——最初的索拉非尼靶点——和 MKNK 激酶分别由于抑制剂诱导的转激活和负反馈而成为药理学上的缺陷。通过逐步的人工合成改进,我们报告了一类新的“肿瘤校准抑制剂”,它们在果蝇和人 MTC 异种移植模型中具有独特的多药理学作用和显著提高的治疗指数。该平台为创造新的高效低毒药物提供了一种合理的方法。