New Noisy Models to Molecular Signaling

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by Sophie Zhu

Biology class after biology class, we are reminded of how cell communication works—a gene encodes a protein that, in turn, regulates cell growth or function by flicking on and off certain chunks of the cell genome. In the old biology curriculum, we learned these proteins have specific binding sites that lock tightly into corresponding specific binding sites of receptors, surmised as the “lock-and-key model.” In 2000, a graduate student and his mentor at Princeton University had successfully inserted a set of genes into E. coli bacteria that induced the cells’ fluorescence—namely, the genes invoked the production of a certain protein that made the cells glow. Yet recently, we have learned the correspondence between these proteins and receptors may be much more versatile and flexible.

The newest model, coined “the combinatorial model” for its much more diverse range of possible protein-receptor interactions, highlights a key misconception in the mechanism of molecular signaling. Often, we believe signaling proteins like growth proteins float around in the human body before encountering and locking into an extremely specific receptor, causing, in the case of growth factor proteins called BMPs, cartilage development, for instance. In other words, the receptor and the protein’s identities utterly fix function. However, in reality, the consequences of this cell communication depends vastly on cell type or, even with cells of the same type, the stage of development the cell is at. In short, these proteins are “the messengers, not the messages.”

In the case of BMPs, one Caltech research team exemplified the variety of outcomes a BMP-receptor interaction could produce. Sometimes 2 receptor subunits were equally as effective as 3 receptor subunits, and sometimes interchanging receptor subunits or BMP proteins halted activity completely, or built upon each other for strengthened effect, or cancelled each other out. Although they could sort the BMP proteins by patterns of interactions, this classification is unreliable and chaotic, further demonstrating the versatility of this new combinatorial model. 

Some biologists believe that this model may be the only pragmatic one in the context of such a dynamic glut of life over so many millions of years on this earth. The high specificity of a cell communication model would make it too vulnerable—one small error would halt its circuitry. The unpredictability of protein and receptor counts would complicate such a system. Plus, through cell division, little details like the precise angle of an amino acid in a receptor’s binding site may be incorrectly reproduced. This could either cause a costly waste of defunct cells or a costly mishap in the cell communication system. 

Moreover, the flexibility of this new model gives ample room for molecular signaling networks to evolve. The more pliable and spacious a system is, the more easily and quickly it can develop new functions. This, says a developmental biologist at Harvard Medical School, is because the machinery would possess a higher tolerance of mutations in its cogs.

This new model has important consequences for the field of pharmacology. It suggests that drugs must be developed beyond a one-hit panacea for a specific illness—the proteins they target may produce different, potentially harmful, effects in different areas of the body.

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