Kinases are enzymes that catalyze the transfer of the g-phosphate group of ATP onto a substrate. They mediate a vast number of cell signaling pathways that regulate critical cellular activities, including proliferation, survival, apoptosis, metabolism, transcription and differentiation. One can imagine that deregulation of these important kinase signaling networks would wreak havoc and result in myriad diseases; on the bright side, kinases present as relatively obvious and very promising drug targets. Indeed, kinases have become one of the most intensively pursued target classes in cancer research. BCR-Abl was the first kinase for which a small-molecule inhibitor, imatinib, was successfully approved by the Food and Drug Administration (FDA) in 2001 for the treatment of patients with chronic myeloid leukemia. This kinase inhibitor, fondly called the “magic bullet” was a revolutionary success for the field, and epitomized the holy grail of targeted therapy in cancer. Since then, interest in kinases has surged, as reflected by the number of publications on the biology of kinases, identification of numerous small-molecular kinase inhibitors, and the approval of 28 small-molecule kinase inhibitors by the US FDA to date, half of which were approved in the past few years.
Nevertheless, abundance of data and inhibitory compounds come with an inherent set of challenges. Human kinases have highly similar three-dimensional structures, especially in the catalytically active kinase domain. As a consequence, small-molecule kinase inhibitors tend to be promiscuous, inhibiting several targets beside the intended one, and cause undesired off-target effects that can result in dire consequences. Although several groups have performed large-scale kinase inhibitor screens to inform the selection, use and analysis of these compounds, these data are decentralized, and do not share a common methodology when it comes to analysis. As such, despite the wealth of research, there still remains the hurdle of identifying the right kinase inhibitor for a biological task, not a small feat given the countless possible outcomes.
Dr. Taran Gujral from the Human Biology Division, together with a graduate student in his lab, Thomas Bello, tackled this challenge of identifying which compound to use for inhibiting a chosen signaling pathway by creating KInhibition, an online portal that allows publicly-available datasets to be searched for selective inhibitors for a specific kinase or group of kinases. Their work was recently published in iScience. Thomas Bello explained: “The goal of KInhibition is to leverage existing data in the decision making process of selecting a kinase inhibitor. We wanted to make already-available data more useful, and to allow researchers to make data-driven decisions about which kinase inhibitor to use.”
Publically available data from four kinase inhibitor screens were used. To consolidate these data, often presented as a matrix of drug-target interactions, the authors developed a “KInhibition Selectivity Score”, which Bello describes: “The KInhibition Selectivity score was born out of necessity. We had a very specific format of data from which to start, and very specific information we wanted to capture and summarize from that data. None of the existing metrics for inhibitors could quite accomplish all of this, so we developed one to best suit our needs for this project.” Experimental efforts to validate the usefulness of this score, both explicitly and through the application of KInhibition to other research projects have shown promising results so far. The KInhibition Selectivity Score provides the user with the most pertinent information and control when it comes to deciding which compound to use. Furthermore, the KInhibition app is run on a web browser in its entirety, eliminating the need to upload or download data. KInhibition also allows users to visualize their analyses in the form of heat maps, easily download data, and include other datasets when they become available.
Taken together, this robust and easy-to-use online portal does the important job of consolidating the wealth of biological information on kinase inhibition, giving researchers a powerful tool that have the potential to greatly accelerate drug therapeutic applications. Bello enthused about what is to come following the launch of this online portal: “Our most immediate goal is to make this available to as many people as possible, get people using this tool, and see what their thoughts are. While the development of this tool was not a community-driven effort in the strictest sense, this tool is meant to be a community-focused portal designed to connect researchers with the resources they need to make informed decisions.”
Bello T and Gujral TS. 2018. KInhibition: A kinase inhibitor selection portal. iScience Sept 18; 8:49-53.
Funding was provided by the National Institutes of Health, and the Pacific Northwest Prostate Cancer SPORE.
Basic Sciences Division
Human Biology Division
Maggie Burhans, Ph.D.
Public Health Sciences Division
Vaccine and Infectious Disease Division
Clinical Research Division
Julian Simon, Ph.D.
Clinical Research Division
and Human Biology Division
Arnold Digital Library