Motif-guided identification of KRAS-interacting proteins.

Background: For decades, KRAS has always been a huge challenge to the field of drug discovery for its significance in cancer progression as well as its difficulties in being targeted as an "undruggable" protein. KRAS regulates downstream signaling pathways through protein-protein interactions, whereas many interaction partners of KRAS remain unknown.

Results: We developed a workflow to computationally predict and experimentally validate the potential KRAS-interacting proteins based on the interaction mode of KRAS and its known binding partners. We extracted 17 KRAS-interacting motifs from all experimentally determined KRAS-containing protein complexes as queries to identify proteins containing fragments structurally similar to the queries in the human protein structure database using our in-house protein-protein interaction prediction method, PPI-Miner. Finally, out of the 78 predicted potential interacting proteins of KRAS, 10 were selected for experimental validation, including BRAF, a previously reported interacting protein, which served as the positive control in our validation experiments. Additionally, a known peptide that binds to KRAS, KRpep-2d, was also used as a positive control. The predicted interacting motifs of these 10 proteins were synthesized to perform biolayer interferometry assays, with 4 out of 10 exhibiting binding affinities to KRAS, and the strongest, GRB10, was selected for further validation. Additionally, the interaction between GRB10 (RA-PH domain) and KRAS was confirmed via immunofluorescence and co-immunoprecipitation.

Conclusions: These results demonstrate the effectiveness of our workflow in predicting potential interacting proteins for KRAS and deepen the understanding of KRAS-driven tumor mechanisms and the development of therapeutic strategies.