A Computational Approach for Prioritizing Selection of Therapies Targeting Drug Resistant Variation in Anaplastic Lymphoma Kinase

Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase implicated as a driver of a number of cancer types, and activates cellular pathways involved in cell proliferation and differentiation. Tyrosine kinase inhibitors (TKIs) are a small molecule therapeutic that blocks ALK function, but tumor evolution leads to the rapid emergence of drug resistant somatic variation and necessitates selection of a new treatment strategy. Computational simulations of protein:drug interactions were used to investigate the impact of seven drug resistant mutations on binding to eleven TKIs approved, or under investigation, for treatment of ALK positive cancers. The results show variant specific disruptions to TKI molecular interactions, and demonstrate the potential to aid prioritization of therapeutic interventions. Validation remains a challenge due to the complex dependence of biomolecular interactions on the local biophysical environment, but improvements to the underlying structural model and continued curation efforts will improve the clinical utility of computational predictions.