Cotranslational folding allows misfolding-prone proteins to circumvent deep kinetic traps

Bitran, Amir; Jacobs, William M.; Zhai, Xiadi; Shakhnovich, Eugene I.

doi:10.1073/pnas.1913207117

Cited by 49 publications

(56 citation statements)

References 63 publications

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“…The results of our simulations thus demonstrate the feasibility of a protein folding machine. Some recently published results, including studies of the role of the exit tunnel in nascent chain folding (32)(33)(34)(35)(36) and of direct coupling between ATP hydrolysis and protein refolding by the chaperones of the HSP70 family (37)(38)(39), may be also interpreted as evidence of protein folding in vivo being an active process.…”

Section: Discussionmentioning

confidence: 99%

Energy-dependent protein folding: modeling how a protein folding machine may work

Sahakyan

Nazaryan

Mushegian

et al. 2020

Preprint

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Proteins fold robustly and reproducibly in vivo, but many cannot fold in vitro in isolation from cellular components. The pathways to proteins’ native conformations, either in vitro or in vivo, remain largely unknown. It is possible that the slow progress in recapitulating protein folding pathways in silico is due not to a lack of computational power but to fundamental deficiencies in our understanding of folding as it occurs in nature. We consider the possibility that protein folding in living cells may not be driven solely by the decrease in Gibbs free energy. We propose that protein folding in vivo should be modeled as an active energy-dependent process and that the mechanism of action of such a protein-folding machine might include direct manipulation of the peptide backbone. Considering the rotating motion of the tRNA 3’-end in the peptidyl transferase center of the ribosome, we hypothesized that this motion might introduce rotation to the nascent peptide and influence the peptide’s folding pathway. We tested whether the formation of protein native conformations could be facilitated by the application of mechanical force to rotate one part of the folding polypeptide while simultaneously restricting rotation of another part of the peptide. We ran molecular dynamics simulations augmented by the application of torsion to the peptide backbones. The directional rotation of the C-terminal amino acid, with the simultaneous limitation of the N-terminal amino acid movements, indeed facilitated the formation of native structures in five diverse alpha-helical peptides. These simulations demonstrate the feasibility of a protein-folding machine.Significance StatementWe show that in silico formation of the native helical structure in proteins can be substantially facilitated by simulating the application of mechanical rotation to the peptide backbone. When the backbone is manipulated by simultaneous directional rotation of one terminus and movement restriction of the other terminus, the peptide no longer behaves as a freely jointed chain, and its folding behavior changes dramatically. These results open a previously unexplored avenue in modeling and understanding the mechanism of protein folding that, in our model, is an intrinsically non-equilibrium process.

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Section: Discussionmentioning

confidence: 99%

Energy-dependent protein folding: modeling how a protein folding machine may work

Sahakyan

Nazaryan

Mushegian

et al. 2020

Preprint

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“…Fig. S10 also shows the energies of native conformations for nascent chain lengths [15][16][17][18][19][20][21][22][23][24][25][26][27]. For proteins in Group 2, we observe that the C-terminal residues for the evolved sequences contribute a greater fraction of the stabilization of the native state than is the case for the unevolved sequences.…”

Section: Two Opposing Strategies For Reaching the Native Statementioning

confidence: 90%

“…The study from our group examined E. coli proteins in particular, finding that conserved rare codons are often located downstream of cotranslational folding intermediates that were identified using a native-centric model of cotranslational protein folding (20). In a subsequent computational study using a more realistic all-atom sequence-based potential, we found that the positions of slowly translating, rare codons could correspond to nascent chains lengths that exhibit stable partly folded states as well as fast folding kinetics (22).…”

Section: Introductionmentioning

confidence: 97%

Effect of protein structure on evolution of cotranslational folding

Zhao

Jacobs

Shakhnovich

2020

Preprint

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Cotranslational folding is expected to occur when the folding speed of the nascent chain is faster than the translation speed of the ribosome, but it is difficult to predict which proteins cotranslationally fold. Here, we simulate evolution of model proteins to investigate how native structure influences evolution of cotranslational folding. We developed a model that connects protein folding during and after translation to cellular fitness. Model proteins evolved improved folding speed and stability, with proteins adopting one of two strategies for folding quickly. Low contact order proteins evolve to fold cotranslationally. Such proteins adopt native conformations early on during the translation process, with each subsequently translated residue establishing additional native contacts. On the other hand, high contact order proteins tend not to be stable in their native conformations until the full chain is nearly extruded. We also simulated evolution of slowly translating codons, finding that slowing translation at certain positions enhances cotranslational folding. Finally, we investigated real protein structures using a previously published dataset that identified evolutionarily conserved rare codons in E. coli genes and associated such codons with cotranslational folding intermediates. We found that protein substructures preceding conserved rare codons tend to have lower contact orders, in line with our finding that lower contact order proteins are more likely to fold cotranslationally. Our work shows how evolutionary selection pressure can cause proteins with local contact topologies to evolve cotranslational folding. Statement of significanceSubstantial evidence exists for proteins folding as they are translated by the ribosome. Here we developed a biologically intuitive evolutionary model to show that avoiding premature protein degradation can be a sufficient evolutionary force to drive evolution of cotranslational folding. Furthermore, we find that whether a protein's native fold consists of more local or more nonlocal contacts affects whether cotranslational folding evolves. Proteins with local contact topologies are more likely to evolve cotranslational folding through nonsynonymous mutations that strengthen native contacts as well as through synonymous mutations that provide sufficient time for cotranslational folding intermediates to form.

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“…But for larger, more complex proteins, DBFOLD can compute folding pathways at a significantly reduced computational cost relative to direct simulation, which would require unreasonably long simulation times. We quantify this computational speedup for various proteins simulated here and in reference [17] by tallying the total time that was required to run equilibrium simulations to convergence, and to collect sufficient high-temperature unfolding statistics to allow for extrapolation prior to use of DBFOLD (Fig. 7, rightmost column).…”

Section: Determining Validity Of Conditions I and Iimentioning

confidence: 99%

“…Such intermediates can be detrimental in vivo, where they may be degraded, form toxic oligomers, or aggregate, potentially leading to loss of fitness and/or disease [1][2][3][4][5][6][7]. Organisms deploy various cellular mechanisms to mitigate protein misfolding including chaperones [4,[8][9][10] and co-translational folding on the ribosome [5,[11][12][13][14][15][16][17], which may be enhanced by slowly translating codons located at nascent chain lengths that show optimal folding properties [15][16][17]. Despite the fact that non-native folding intermediates exert widespread and significant consequences, we have yet to develop a detailed atomstic understanding of how they slow folding, and how cellular mechanisms reduce their formation and detrimental effects.…”

Section: Introductionmentioning

confidence: 99%

DBFOLD: An efficient algorithm for computing folding pathways of complex proteins

Bitran

Jacobs²,

Shakhnovich

2020

Preprint

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Atomistic simulations can provide valuable, experimentally-verifiable insights into protein folding mechanisms, but existing ab initio simulation methods are restricted to only the smallest proteins due to severe computational speed limits. The folding of larger proteins has been studied using native-centric potential functions, but such models omit the potentially crucial role of non-native interactions.Here, we present an algorithm, entitled DBFOLD, which can predict folding pathways for a wide range of proteins while accounting for the effects of non-native contacts. In addition, DBFOLD can predict the relative rates of different transitions within a protein’s folding pathway. To accomplish this, rather than directly simulating folding, our method combines equilibrium Monte-Carlo simulations, which deploy enhanced sampling, with unfolding simulations at high temperatures. We show that under certain conditions, trajectories from these two types of simulations can be jointly analyzed to compute unknown folding rates from detailed balance. This requires inferring free energies from the equilibrium simulations, and extrapolating transition rates from the unfolding simulations to lower, physiologically-reasonable temperatures at which the native state is marginally stable. As a proof of principle, we show that our method can accurately predict folding pathways and Monte-Carlo rates for the well-characterized Streptococcal protein G. We then show that our method significantly reduces the amount of computation time required to compute the folding pathways of large, misfolding-prone proteins that lie beyond the reach of existing direct simulation methods. Our algorithm, which is available online, can generate detailed atomistic models of protein folding mechanisms while shedding light on the role of non-native intermediates which may crucially affect organismal fitness and are frequently implicated in disease.Author summaryMany proteins must adopt a specific structure in order to function. Computational simulations have been used to shed light on the mechanisms of protein folding, but unfortunately, realistic simulations can typically only be run for small proteins, due to severe limits in computational speed. Here, we present a method to solve this problem, whereby instead of directly simulating folding from an unfolded state, we run simulations that allow for computation of equilibrium folding free energies, alongside high temperature simulations to compute unfolding rates. From these quantities, folding rates can be computed using detailed balance. Importantly, our method can account for the effects of nonnative contacts which transiently form during folding and must be broken prior to adoption of the native state. Such contacts, which are often excluded from simple models of folding, may crucially affect real protein folding pathways and are often observed in folding intermediates implicated in disease.

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Cotranslational folding allows misfolding-prone proteins to circumvent deep kinetic traps

Cited by 49 publications

References 63 publications

Energy-dependent protein folding: modeling how a protein folding machine may work

Energy-dependent protein folding: modeling how a protein folding machine may work

Effect of protein structure on evolution of cotranslational folding

DBFOLD: An efficient algorithm for computing folding pathways of complex proteins

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