K-Map

K-Map maps query kinases to kinase inhibitors using quantitative inhibitor activity profiles to identify candidate inhibitors and combinations for studying kinase-driven phenotypes such as EGFR-TKI resistance in NSCLC.

Key Features:

• Kinase–inhibitor connectivity: Connects query kinases with kinase inhibitors based on quantitative profiles of inhibitor activities.
• Omics input support: Accepts kinase sets derived from high-throughput "omics" experiments for downstream inhibitor matching.
• Integration of functional data: Integrates functional genetics screen data and RNA-seq data to prioritize biologically relevant kinases.
• Identification of candidate compounds: Links prioritized kinases to potential compounds for experimental validation and repurposing.
• Support for combination strategies: Facilitates identification of rational drug combinations to address resistance mechanisms.

Scientific Applications:

• Candidate inhibitor discovery: Identification of potential kinase inhibitors for sets of kinases derived from genomics and functional screens.
• EGFR-TKI resistance analysis: Application to EGFR-TKI resistant non-small-cell lung cancer (NSCLC) to identify essential kinases driving resistance.
• Compound nomination and validation: Linking essential kinases to compounds led to nomination of bosutinib and testing combinations with gefitinib showing additive and synergistic effects in resistant cell lines.
• Drug repurposing and personalized strategies: Enables repurposing of existing kinase inhibitors and supports development of personalized combination therapies for cancer.

Methodology:

Computationally connects query kinases to kinase inhibitors using quantitative inhibitor activity profiles and integrates functional genetics screen data with RNA-seq data to identify essential kinases and link them to potential compounds.