An optimal set of inhibitors for Reverse Engineering via Kinase Regularization

Abstract

We present a comprehensive resource of 257 kinase inhibitor profiles against 365 human protein kinases using gold-standard kinase activity assays. We show the utility of this dataset with an improved version of Kinome Regularization (KiR) to deconvolve protein kinases involved in a cellular phenotype. We assayed protein kinase inhibitors against more than 70% of the human protein kinome and chose an optimal subset of 58 inhibitors to assay at ten doses across four orders of magnitude. We demonstrate the effectiveness of KiR to identify key kinases by using a quantitative cell migration assay and updated machine learning methods. This approach can be widely applied to biological problems for which a quantitative phenotype can be measured and which can be perturbed with our set of kinase inhibitors.

Polypharmacological Re-programming of Tumor-associated Macrophages Restores Antitumor Immunity

“…The selected kinase inhibitors cover 289 kinases from various kinase families, with lower than 50% residual activities at 0.5 µM. The kinase tree was prepared using KinMap (Eid et al, 2017) (Rata et al, 2020). Also, see Figure S4A and Table S2.…”

“…The phase contrast and red fluorescent images were taken every 2 hours over 3-5 days using IncuCyte Zoom instrument. The target kinase profiles of BMS-794833 in acellular system were described in Rata, et al(Rata et al, 2020).…”

“…Figure 5 BMS-794833 targets multiple signaling pathways in TAMs(A) Target kinase profile of BMS-794833. Residual activities of kinases under the presence of BMS-794833 at 0.5 µM were evaluated in in vitro acellular system with synthetic substrates(Rata et al, 2020). Also, see FigureS4Aand TableS2.…”

Identification of Kinases Activated by Multiple Pro-Angiogenic Growth Factors

“…To identify kinases that are used by endothelial cells regardless of the growth factor input, we applied KIR (Rata et al 2020; Taranjit Singh Gujral, Peshkin, and Kirschner 2014; Taranjit S. Gujral et al 2014). KIR consists of two steps, first measuring the quantitative effects of 58 kinase inhibitors on proliferation rate in the presence of FGF2, VEGFA, and HGF.…”

“…The assay is used to screen ∼30 reported angiogenic growth factors for effects on proliferation and identify three that produce a robust increase in proliferation. We then assay the effects of a carefully chosen panel of kinase inhibitors, which when combined with KIR, a recently developed machine learning method (Taranjit Singh Gujral, Peshkin, and Kirschner 2014; Rata et al 2020; Taranjit S. Gujral et al 2014), implicates specific kinases as important in DMEC proliferation in response to specific growth factors. Focusing on the intersection of the implicated kinases in each growth factor tested, we identify kinases that are central to endothelial cell proliferation regardless of the growth factor input.…”