A Proposed Mechanism for in vivo Programming Transmembrane Receptors

Abstract

AbstractTransmembrane G-protein coupled receptors (GPCRs) are ideal drug targets because they resemble, in function, molecular microprocessors for which outcomes (e.g. disease pathways) can be controlled by inputs (extracellular ligands). The inputs here are ligands in the extracellular fluid and possibly chemical signals from other sources in the cellular environment that modify the states of molecular switches, such as phosphorylation sites, on the intracellular domains of the receptor. Like in an engineered microprocessor, these inputs control the configuration of output switch states that control the generation of downstream responses to the inputs.Many diseases with heterogeneous prognoses including, for example, cancer and diabetic kidney disease, require precise individualized treatment. The success of precision medicine to treat and cure disease is through its ability to alter the microprocessor outputs in a manner to improve disease outcomes. We previously established ab initio a model based on maximal information transmission and rate of entropy production that agrees with experimental data on GPCR performance and provides insight into the GPCR process. We use this model to suggest new and possibly more precise ways to target GPCRs with potential new drugs.We find, within the context of the model, that responses downstream of the GPCRs can be controlled, in part, by drug ligand concentration, not just whether the ligand is bound to the receptor. Specifically, the GPCRs encode the maximum ligand concentration the GPCR experiences in the number of active phosphorylation or other switch sites on the intracellular domains of the GPCR. This process generates a memory in the GPCR of the maximum ligand concentration seen by the GPCR. Each configuration of switch sites can generate a distinct downstream response bias. This implies that cellular response to a ligand may be programmable by controlling drug concentration. The model addresses the observation paradox that the amount of information appearing in the intracellular region is greater than amount of information stored in whether the ligand binds to the receptor. This study suggests that at least some of the missing information can be generated by the ligand concentration. We show the model is consistent with assay and information-flow experiments.In contrast to the current view of switch behavior in GPCR signaling, we find that switches exist in three distinct states: inactive (neither off nor on), actively on, or actively off. Unlike the inactive state, the active state supports a chemical flux of receptor configurations through the switch, even when the switch state is actively off. Switches are activated one at a time as ligand concentration reaches threshold values and does not reset because the ligand concentration drops below the thresholds. These results have clinical relevance. Treatment with drugs that target GPCR-mediated pathways can have increased precision for outputs by controlling switch configurations. The model suggests that, to see the full response spectrum, fully native receptors should be used in assay experiments rather than chimera receptors.Inactive states allow the possibility for novel adaptations. This expands the search space for natural selection beyond the space determined by pre-specified active switches.