From flexibility to function: Molecular dynamics simulations of conformational changes in chaperones and photoreceptors

Proteins are uniquely-shaped macromolecules that function as biological machines, and regulate a living cell’s behavior. Crucial to protein function is the folding of the polypeptide chain into a unique well-defined three-dimensional conformation. In complex cell environments, the spontaneous unassisted folding process is particularly prone to misfolding, leading to several neurodegenerative diseases, e.g., Alzheimer’s disease. Molecular chaperones are special proteins that suppress these anomalies by interacting with the newly synthesised polypeptide chains to assist in their folding. Trigger factor (TF) is an ATP-independent chaperone, characterised in the cytosol as well as near the ribosome exit tunnel in bacteria and chloroplasts. It is known to bind unfolded and partially folded protein chains, and slow down or delay the onset of their folding. Its flexibility and promiscuous surface allow TF to interact with substrates with diverse compositions and sizes, without the need for an ATP cycle to switch between encapsulation and liberation of client proteins. In this work, we present a model for TF as a highly adaptive chaperone, in which TF grabs the non-folded and partially folded chains with its domain tips as they form, transfers them to its cradle to encapsulate them so that they are protected against misfolding interactions with other domains and/or proteins. This work provides a framework to employ machine learning methods and elastic network coarse-grained models to complex TF-substrate systems, and explore TF’s chaperone function in the cytosol of bacterial cells.