Selectivity filters to edit out deleterious side effects in kinase inhibitors.

As the molecular etiology of cancer unravels, revealing the heterogeneous nature of the malignancy, multi-target drug treatments are more frequently advocated. Such therapeutic avenues often target kinases, the basic signal transducers in the cell. Because kinases share common evolutionary backgrounds, they also share many structural attributes, making it difficult for molecular targeted therapy to distinguish between paralogs. Thus, kinase inhibitors (KIs) tend to have undesired cross-reactivities, resulting in potentially lethal side effects. The health risks are obviously higher in these multi-pronged treatments when contrasted with the effects of more selective therapeutic agents. Using a nonconserved physicochemical biomarker, we present a rationally designed molecular filter that enables the control of specificity and the development of adjuvant drugs to edit out the side effects of the primary therapeutic agent. These editors work by overlapping therapeutically with the primary drug in cancer cells, while interfering with toxicity-related signaling pathways recruited by the primary drug in off-target cells. We then examine the possible application of these filtering methods to specifically target kinases when they present idiosyncratic cancer-related mutations. Such applications open the door to engineer personalized drugs tailored to the genetic makeup of the patient. These various methods of enhancing efficacy and safety show some degree of modularity, allowing drug designers to utilize multiple techniques and various drug combinations to create the safest and most powerful treatment for any given therapeutic scenario.