Molecular Simulations of Cotranslational Protein Folding: Fragment Stabilities, Folding Cooperativity, and Trapping in the Ribosome

Abstract

Although molecular simulation methods have yielded valuable insights into mechanistic aspects of protein refolding in vitro, they have up to now not been used to model the folding of proteins as they are actually synthesized by the ribosome. To address this issue, we report here simulation studies of three model proteins: chymotrypsin inhibitor 2 (CI2), barnase, and Semliki forest virus protein (SFVP), and directly compare their folding during ribosome-mediated synthesis with their refolding from random, denatured conformations. To calibrate the methodology, simulations are first compared with in vitro data on the folding stabilities of N-terminal fragments of CI2 and barnase; the simulations reproduce the fact that both the stability and thermal folding cooperativity increase as fragments increase in length. Coupled simulations of synthesis and folding for the same two proteins are then described, showing that both fold essentially post-translationally, with mechanisms effectively identical to those for refolding. In both cases, confinement of the nascent polypeptide chain within the ribosome tunnel does not appear to promote significant formation of native structure during synthesis; there are however clear indications that the formation of structure within the nascent chain is sensitive to location within the ribosome tunnel, being subject to both gain and loss as the chain lengthens. Interestingly, simulations in which CI2 is artificially stabilized show a pronounced tendency to become trapped within the tunnel in partially folded conformations: non-cooperative folding, therefore, appears in the simulations to exert a detrimental effect on the rate at which fully folded conformations are formed. Finally, simulations of the two-domain protease module of SFVP, which experimentally folds cotranslationally, indicate that for multi-domain proteins, ribosome-mediated folding may follow different pathways from those taken during refolding. Taken together, these studies provide a first step toward developing more realistic methods for simulating protein folding as it occurs in vivo.

Prediction of variable translation rate effects on cotranslational protein folding

“…3c) to the folding (5) (5) curve that would result from averaging over a large number of independent, stochastically translating ribosomes.…”

“…To avoid these potentially dangerous possibilities and facilitate the folding process 2 , a variety of quality control mechanisms are associated with translating ribosomes, including those involving molecular chaperones and other ancillary factors 1 . An additional level of control is provided by the opportunity for proteins to fold during synthesis [3][4][5][6] , thus potentially enhancing folding yields 7 and avoiding misfolded or intermediate species 8,9 . Given its importance, it is not surprising that the cotranslational folding process can be regulated by the modulation of the rates at which successive amino acids are covalently attached to the nascent chain during synthesis.…”

Multiple folding pathways of proteins with shallow knots and co-translational folding

“…It would be interesting to consider a realistic variant of co-translational folding -one that takes into account confinement. This is because the ribosome spawns proteins into molecularly sculpted chambers [39], which parallels the physics of encapsulation within GroEL-GroES chaperonins considered by Lim and Jackson [14] in the context of deeply knotted proteins. Figure 1: The folding mechanisms in 2EFV found in ref.…”

Protein folding simulations: From coarse‐grained model to all‐atom model

“…The territory of computer simulations has even been expanded to large protein complex or molecular machines. For example, it has been used to study the stability of nucleosomes, the dynamics of ion channels and virus capsides, the motion of molecular motors, and the synthesis process of proteins in ribosome (182)(183)(184)(185)(186)(187)(188)(189)(190). With the continuing improvement in computational power as well as in methodology, both temporal and spatial region accessible to simulations will be broadened further; it can be expected that computer simulations will prove invaluable in an even wider field and provide more exciting insights into structural biology.…”