Cyclin-dependent kinases play critical roles in regulating the cell cycle. Thus, inhibition of CDKs should arrest cell proliferation and trigger cell death in tumor cells.
AstraZeneca (Wilmington, DE) is utilizing structure-guided methods to design CDK4 inhibitors. According to David Buttar, Ph.D., scientist, some tumors have lost natural CDK4 control mechanisms.
Since CDK4 is unsolved at present, AstraZeneca's approach is to exploit CDK2 crystallographic information as a surrogate for CDK4 design. Additionally, Dr. Buttar indicates that one way to look for structural surrogates is to classify kinases by their inhibitory profile.
"The past decade has witnessed an explosion in the number of three-dimensional protein small molecule structures from experimental as well as in silico approaches," Juswinder Singh, associate director, computational drug design group at Biogen Idec, explains.
"The use of profiles enables a more empirical approach to leveraging the experimental data to more effectively filter these massive in silico datasets. The profile approach is broadly applicable to either specific drug targets or other gene families."
According to Singh, "The gene family concept is emerging as a powerful paradigm to accelerate drug discovery through leveraging structural insights into druggability and transferability of chemotypes amongst related drug targets.
"The protein kinases exemplify a family where the potential exists to accelerate lead discovery and optimization by inferring between the massive amount of structural and chemical data from gene family members.
"We have developed novel tools to analyze protein kinase inhibitors and identified key interaction signatures that seem to be conserved across most of the kinase inhibitors that have been solved using x-ray crystallography. These signatures have been used by us to virtually screen for novel inhibitors."
The concept of a kinase profile rather than specific kinase inhibition may provide a better method of obtaining a pharmacological response. Singh and colleagues have developed a profile-based structural interaction fingerprint technology.
The profile is a sequence position-specific scoring matrix encoding the probability of finding any of the 20 amino acids at a specific position in the target, notes Singh. The analysis derives a position-dependent profile of the probability that a given interaction is present at a specific site.
Singh believes that profile-based methods provide a superior enrichment of kinase inhibitors relative to traditional scoring approaches.
"At present, there are no effective tools to leverage the information gained from protein inhibitor complexes. This p-SIFt profile approach fills this capability gap, and provides a powerful mechanism to screen for novel inhibitors using virtual screening and also identify selective inhibitors."