Learning of signaling networks: molecular mechanisms
This work addresses a gap in molecular biology for researchers in cell signaling and AI, though it is incremental as it synthesizes existing knowledge into a hypothesis.
The paper tackles the problem of understanding molecular learning mechanisms in non-neuronal cells, proposing that processes like protein conformational memory and signaling cascades constitute a generalized Hebbian learning process in single cells.
Molecular processes of neuronal learning have been well-described. However, learning mechanisms of non-neuronal cells have not been fully understood at the molecular level. Here, we discuss molecular mechanisms of cellular learning, including conformational memory of intrinsically disordered proteins and prions, signaling cascades, protein translocation, RNAs (microRNA and lncRNA), and chromatin memory. We hypothesize that these processes constitute the learning of signaling networks and correspond to a generalized Hebbian learning process of single, non-neuronal cells, and discuss how cellular learning may open novel directions in drug design and inspire new artificial intelligence methods.