We analyzed an extensive data set of 3000 Janssen kinase inhibitors (spanning some 40 therapeutic projects) profiled at 414 kinases in the DiscoverX KINOMEscan to better understand the necessity of using such a full kinase panel versus simply profiling one’s compound at a much smaller number of kinases, or mini kinase panel (MKP), to assess its selectivity. To this end, we generated a series of MKPs over a range of sizes and of varying kinase membership using Monte Carlo simulations. By defining the kinase hit index (KHI), we quantified a compound’s selectivity based on the number of kinases it hits. We find that certain combinations (rather than a random selection) of kinases can result in a much lower average error. Indeed, we identified a focused MKP with a 45.1% improvement in the average error (compared to random) that yields an overall correlation of R² = 0.786–0.826 for the KHI compared to the full kinase panel value. Unlike using a full kinase panel, which is both time and cost restrictive, a focused MKP is amenable to the triaging of all early stage compounds. In this way, promiscuous compounds are filtered out early on, leaving the most selective compounds for lead optimization.

中文翻译：

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确定聚焦的微型激酶面板，用于早期识别选择性激酶抑制剂

我们在DiscoverX KINOME扫描中分析了在414种激酶中分布的3000种Janssen激酶抑制剂的广泛数据集（涵盖约40个治疗项目），以更好地了解使用这样一个完整的激酶组而不是简单地对一个化合物进行少量分析的必要性激酶，或迷你激酶组（MKP），以评估其选择性。为此，我们使用蒙特卡洛模拟方法在一系列大小和激酶成员范围内生成了一系列MKP。通过定义激酶命中指数（KHI），我们基于化合物命中的激酶数量来定量化合物的选择性。我们发现激酶的某些组合（而不是随机选择）可以导致低得多的平均误差。实际上，我们确定了一个聚焦的MKP，其平均误差（与随机误差相比）提高了45.1％，与完整的激酶组值相比，KHI的总体相关性为R ² = 0.786–0.826。与使用时间和成本均受限制的全激酶检测方法不同，聚焦的MKP可用于所有早期化合物的分类。这样，混杂化合物会尽早被滤出，留下最有选择性的化合物进行铅优化。