Exploring the Molecular Pathways of the Activation Process on PPARγ Recurrent Bladder Cancer Mutants

The intricate involvement of Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) in vital processes such as glucose homeostasis and adipogenesis is well established. However, its multifaceted role in cancer, particularly in luminal bladder cancer, remains a subject of intense debate. In this context, PPARγ’s overexpression and activation have been implicated in tumorigenesis. Notably, specific gain-of-function mutations (M280I, I290M, and T475M) within PPARγ’s ligand-binding domain have been pinpointed in bladder cancer, correlating with receptor activation. Nonetheless, the underlying molecular pathways prompted by these mutations remain obscure. Here, we employed a dual-basin structure-based model (db SBM) to unveil the intricate conformational dynamics that underlie the transition between PPARγ’s inactive and active states. Additionally, we explored the effects of the M280I, I290M, and T475M mutations on this pivotal process. Our findings concur with existing literature, revealing heightened ligand-independent transcriptional activity in the I290M and T475M mutants compared to other variants. Importantly, both mutants displayed enhanced stabilization of the active state relative to the wild-type receptor, and the I290M mutation promoted a remarkably specific transition route, rendering it a prime candidate for further investigation. Electrostatic analysis pinpointed the pivotal role of residues K303 and E488 in the activation cascade of I290M. This insight was substantiated by biophysical assays, as disruption of the K303-E488 interaction curtailed the thermal stabilization characteristic of the I290M mutation. These findings designate K303 and E488 as potential targets for inhibitors aimed at modulating PPARγ activation, with promising implications for refining bladder cancer prognosis. In sum, our study highlights the remarkable predictive capabilities achieved through the integration of simulation and cheminformatics methods, validated by biochemical experiments, to gain deeper insights into molecular mechanisms of activation and identify target residues for protein modulation.