YES kinase
August 2021
Yes kinase is a non-receptor protein tyrosine kinase that belongs to the Src family kinases (SFK). This target is involved in the regulation of various biological processes such as cell growth and survival. The abnormal activation and/or overexpression of Yes kinase is frequently observed in multiple human cancers, such as colorectal, pancreatic, breast and lung cancer. Despite being considered an important drug target, the market still lacks highly selective inhibitors against it.
The protein 3D structure of Yes kinase has not yet been experimentally resolved. The structure-based studies on this target rely on homology models, which are prepared using close homologs (such as other members of the Src family) as templates. Yes kinase contains multiple protein domains: SH2 (97–144), SH3 (97–144), and a kinase domain (277–526).
Dasatinib and saracatinib are two ATP-competitive inhibitors known to bind to Yes kinase but also to other members of the Src family. Scientists are, therefore, investigating how to achieve more selective Yes inhibitors.
Recently, the full structure of Yes kinase was predicted by the state-of-the-art deep learning algorithm from Google’s DeepMind starting just from its primary sequence. The structure has been published in the Alpha Fold database and provides valuable information to facilitate structure-based inhibitor design. To explore this entirely new structure in 3decision, download its PDB file from the alpha fold database and upload it manually via 3decision‘s web interface. Once registered, you can open the structure in the 3D Viewer and automatically overlay it with PDB structures of other Src family kinases stored in 3decision.
This allows you to quickly identify structural differences within the ATP-binding site. In other words, 3decision helps you gather insights by combining novel with existing structural knowledge to aid efforts in the design of selective small-molecule inhibitors.
Reference: Patel PR, Sun H, Li SQ, et al. Identification of potent Yes1 kinase inhibitors using a library screening approach. Bioorg Med Chem Lett. 2013;23(15):4398-4403. doi:10.1016/j.bmcl.2013.05.072