Topological and energetic factors: what determines the structural details of the transition state ensemble and "en-route" intermediates for protein folding? An investigation for small globular…

By Cecilia Clementi, H. Nymeyer, José N. Onuchic. Journal of Molecular Biology, 2000

1,186 citations recorded by the source corpus.

Recent experimental results suggest that the native fold, or topology, plays a primary role in determining the structure of the transition state ensemble, at least for small, fast-folding proteins. To investigate the extent of the topological control of the folding process, we studied the folding of simplified models of five small globular proteins constructed using a Go-like potential to retain the information about the native structures but drastically reduce the energetic frustration and energetic heterogeneity among residue-residue native interactions. By comparing the structure of the transition state ensemble (experimentally determined by Phi-values) and of the intermediates with those obtained using our models, we show that these energetically unfrustrated models can reproduce the global experimentally known features of the transition state ensembles and "en-route" intermediates, at least for the analyzed proteins. This result clearly indicates that, as long as the protein sequence is sufficiently minimally frustrated, topology plays a central role in determining the folding mechanism.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c7248174cf08e312ad6853cc824042f2f5714dc3

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Citations in the corpus

Mechanical stretching of proteins—a theoretical survey of the Protein Data Bank (2007, methodology): “The full model considered here is kinetically equivalent [115] to the model with the 10–12 contact potentials considered by Clementi et al [116] which was demonstrated to have the two-state kinetics of folding for simple proteins.”
How a protein searches for its site on DNA: the mechanism of facilitated diffusion (2009, neutral): “In the CGMD simulations, the protein was represented by a single bead per residue placed at the Cα position and the protein dynamics was governed by its native-state topology [52, 53].”
Computational modeling of phosphotransfer complexes in two-component signaling. (2010, result): “They have shown to be in high agreement with experimental measurements (Chavez et al ., 2004; Cheung et al ., 2003; Clementi et al ., 2000).”
The protein folding problem. (2008, background): “Models having less atomic detail also emerged to address questions more global and less detailed in nature about protein conformational spaces: (a) The Go model (82), which was intended to see if a computer could find the native structure if native guiding constraints were imposed, is now widely use”
Coarse-grained models for proteins. (2005, background): “According to this point of view, the Gō model works because it represents a perfectly funneled model for folding that correctly includes the topology of the native state [29–31].”
Low-dimensional, free-energy landscapes of protein-folding reactions by nonlinear dimensionality reduction (2006, methodology): “Not surprisingly, the transition state ensemble from the 1-dimensional embedded manifold of the SH3 model is also in good agreement with what obtained using the parameter Q as empirical reaction coordinate (data not shown): previous studies have shown that Q is a robust reaction coordinate for some ”
The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo (2006, methodology): “…with an initial guess for τ , first find the regression solution for β using the multivariate regression methods of L1 shrinkage (described below); second, solve for a new τ that minimizes the prediction error given [49] and g ( β Z ); and third, repeat the first two steps until convergence.”
Water mediation in protein folding and molecular recognition. (2006, methodology): “Folding mechanisms, TSE, and even intermediates (at least for small- and medium-sized proteins) can be predicted using structurebased (Go) models that include a renormalized effect of solvent free energy (22, 27, 28, 80).”
Genomics-aided structure prediction (2012, methodology): “To search for the native protein conformation, we perform simulated annealing using a coarse-grained molecular dynamics model (22) with a single bead per residue, known as the “ C α model.”