AI helped scientists find a human protein by searching shape, not sequence
Researchers searched more than 214 million AlphaFold2 protein models for similar three-dimensional shapes instead of relying only on genetic sequence. Their open-access Nature paper identifies two poorly understood human families of seven-transmembrane proteins. Their structures resemble G-protein-coupled receptors.
Verified 2:45 AM PDT · 2 original sources
The team focused its experiments on TM184C. In cells, TM184C localized to moving vesicles and helped form thin connections that transferred material between cells. Reducing TM184C changed those connections and increased markers of autophagy. A human TM184C gene also restored a related defect in yeast, evidence that part of its function is ancient and conserved.
The shape search found the candidates, but laboratory experiments established the reported function. The researchers tested cell systems and yeast. They did not show that TM184C causes a human disease or that changing it treats cancer. They describe its therapeutic potential as a reason for more study, not as a tested therapy.
Independent labs can test TM184C in tissues and animal models. They can then study what its cell-to-cell exchange does in normal and diseased conditions. Researchers also need to identify the molecules that regulate it. A useful drug target needs a controllable mechanism and a beneficial biological effect, not only a newly named protein family.
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