Exploring RHOGTPases: a computational study of protein-protein interactions and drug design

The CDC42 RHOGTPases subfamily (RHOJ, RHOQ, CDC42) is often overexpressed but rarely mutated in cancer. These GTPases play a critical role in governing both the invasiveness of tumor cells into nearby tissues and the ability of endothelial cells to establish blood vessels within tumors. A key pathway involves the interaction between CDC42 proteins and the serine/threonine kinase PAK, which activates downstream signaling. This interaction is a crucial juncture, initiating and transmitting signaling downstream, ultimately influencing cellular behavior and disease progression. Recognizing the importance of this interaction, computer-aided drug design has been utilized to identify a new class of inhibitor compounds specifically targeting the CDC42 subfamily. This strategic approach aimed to interfere in this critical pathway and potentially impede cancer progression. Moreover, the study utilized alchemical free energy calculations to quantitatively and accurately evaluate the effect of mutations at the protein–protein interface, using the CDC42/PAK interaction as a test case. The study demonstrated an excellent agreement between computed and experimental data on binding affinity. A meticulous analysis of the sidechain conformations of the mutated residues was crucial in enhancing the accuracy of the computed estimates, effectively addressing limitations associated with sampling. This study underscored the advantage of integrating alchemical free energy calculations into the design of experimental mutagenesis studies, highlighting the potential for this approach to significantly contribute to understand the complex protein interactions and guide drug development strategies. In accordance with these findings, the study extended the analysis to the RHOA/ROCK1 interface, which is also heavily implicated in cancer. Preliminary results from alchemical free energy calculations on RHOA mutants lay the foundation for utilizing this methodology to identify hotspot residues crucial for the interaction between these two proteins. Ultimately, this method has the potential to facilitate the exploration of new targetable interactions, contributing to the development of novel tailored therapeutics.