RiSKs in Computational Modeling of Isoform-Selective RSK Inhibitors

Recent developments around inhibitors of the 90 kDa ribosomal S6 serine/threonine kinases (RSK1-4) have been focused on the optimization of known pan-RSK inhibitors such as SL0101 and BI-D1870. The RSKs are an intriguing target for cancer therapy due to their role as downstream effectors in the MAPK pathway. Herein, we focus on the utilization of computational modeling in inhibitor screening and development for RSK, and we examine computational artifacts in molecular modeling, quantum mechanical calculations, molecular dynamics, and high throughput screening. Variation between RSK structural models is also evident, given the available crystal structures, and liberties in homology modeling and dynamic conformations may capture new targeting approaches for these proteins. Furthermore, pan-kinase inhibitors are often used to target RSK since the four different RSK isoforms share a high degree of homology; however, they have distinct biological actions in cancer. A majority of RSK modeling generalizes the conclusions from one isoform onto the others; therefore, forming accurate isoform specific models containing their subtle differences will be key to the development of isoform-selective inhibitors. This review consolidates existing RSK models and the isoform specific structural differences that have and have not been considered, evaluates inhibition studies that have started to build upon RSK selectivity, including for its isoforms, and assesses other inhibitory binding sites to offer potential pathways forward. The leveraging of these differences through computational methods aims to guide next-generation isoform-selective RSK inhibitors.