K-Map: connecting kinases with therapeutics for drug repurposing and development

Abstract

Protein kinases play important roles in regulating signal transduction in eukaryotic cells. Due to evolutionary conserved binding sites in the catalytic domain of the kinases, most inhibitors that target these sites promiscuously inhibit multiple kinases. Quantitative analysis can reveal complex and unexpected interactions between protein kinases and kinase inhibitors, providing opportunities for identifying multi-targeted inhibitors of specific diverse kinases for drug repurposing and development. We have developed K-Map—a novel and user-friendly web-based program that systematically connects a set of query kinases to kinase inhibitors based on quantitative profiles of the kinase inhibitor activities. Users can use K-Map to find kinase inhibitors for a set of query kinases (obtained from high-throughput ‘omics’ experiments) or to reveal new interactions between kinases and kinase inhibitors for rational drug combination studies.Availability and implementationK-Map has been implemented in python scripting language and the website is freely available at: http://tanlab.ucdenver.edu/kMap.

A review of connectivity map and computational approaches in pharmacogenomics

“…However, for either type of investigations, machine learning [6] and biomedical text mining [7] approaches have been vital to uncover hidden relationships between drugs and potential new indications. Overall, applying these methods on drug perturbation data sets has proven to be beneficial in enhancing the understanding of the connection between genes, drugs and diseases [8][9][10] because such methodologies can lead to generation of novel hypotheses beyond classical pharmacology by translating new knowledge from genomic in vitro screens and cell-based assays to the patients.…”

Study of phosphorylation events for cancer diagnoses and treatment

“…Finally, when obtaining data with mutated kinases, clinicians and scientists are interested in knowledge about which kinase‐inhibitors can be applied for cancer treatments. Currently, a high‐throughput kinase‐inhibitor database is accessible, via K‐MAP (http://tanlab.ucdenver.edu/kMap/kMapv1.0) [78] and can be used to complement and design future clinical assays to study resistances and toxicities.…”

An integrated bioinformatics analysis to dissect kinase dependency in triple negative breast cancer

“…We recently developed and implemented K-Map that systematically connects a kinase profile with a reference kinase inhibitor database and predicts the most effective inhibitor for a queried kinase profile [ 26 , 27 ]. The K-Map consists of three key components: (1) a reference database that contains a set of kinase inhibitors profiles; (2) a query signature; and (3) a pattern matching algorithm or similarity metric defined between a query signature and a reference kinase inhibitor profile to quantify the connection (or similarity) between the interactions of kinases and inhibitors.…”

“…We employed our recently developed Kinase Addiction Ranker (KAR) to integrate these data sourcesto dissect kinase dependency in TNBC cell lines[ 25 ]. We then used the kinase dependency predicted by KAR to query K-Map [ 26 , 27 ]for connecting compounds with kinases for individual TNBC lines. For validation, we performed literature search on published experimental data and tested K-Map predictionsin cell lines.…”