Ryan Day

Increasing temperature accelerates protein unfolding without changing the pathway of unfolding.

We have traditionally relied on extremely elevated temperatures (498K, 225 degrees C) to investigate the unfolding process of proteins within the timescale available to molecular dynamics simulations with explicit solvent. However, recent advances in computer hardware have allowed us to extend our thermal denaturation studies to much lower temperatures. Here we describe the results of simulations of chymotrypsin inhibitor 2 at seven temperatures, ranging from 298K to 498K. The simulation lengths vary from 94ns to 20ns, for a total simulation time of 344ns, or 0.34 micros. At 298K, the protein is very stable over the full 50ns simulation. At 348K, corresponding to the experimentally observed melting temperature of CI2, the protein unfolds over the first 25ns, explores partially unfolded conformations for 20ns, and then refolds over the last 35ns. Above its melting temperature, complete thermal denaturation occurs in an activated process. Early unfolding is characterized by sliding or breathing motions in the protein core, leading to an unfolding transition state with a weakened core and some loss of secondary structure. After the unfolding transition, the core contacts are rapidly lost as the protein passes on to the fully denatured ensemble. While the overall character and order of events in the unfolding process are well conserved across temperatures, there are substantial differences in the timescales over which these events take place. We conclude that 498K simulations are suitable for elucidating the details of protein unfolding at a minimum of computational expense.

A consensus view of fold space: Combining SCOP, CATH, and the Dali Domain Dictionary

We have determined consensus protein‐fold classifications on the basis of three classification methods, SCOP, CATH, and Dali. These classifications make use of different methods of defining and categorizing protein folds that lead to different views of protein‐fold space. Pairwise comparisons of domains on the basis of their fold classifications show that much of the disagreement between the classification systems is due to differing domain definitions rather than assigning the same domain to different folds. However, there are significant differences in the fold assignments between the three systems. These remaining differences can be explained primarily in terms of the breadth of the fold classifications. Many structures may be defined as having one fold in one system, whereas far fewer are defined as having the analogous fold in another system. By comparing these folds for a nonredundant set of proteins, the consensus method breaks up broad fold classifications and combines restrictive fold classifications into metafolds, creating, in effect, an averaged view of fold space. This averaged view requires that the structural similarities between proteins having the same metafold be recognized by multiple classification systems. Thus, the consensus map is useful for researchers looking for fold similarities that are relatively independent of the method used to compare proteins. The 30 most populated metafolds, representing the folds of about half of a nonredundant subset of the PDB, are presented here. The full list of metafolds is presented on the Web.

Dynameomics: mass annotation of protein dynamics and unfolding in water by high-throughput atomistic molecular dynamics simulations

The goal of Dynameomics is to perform atomistic molecular dynamics (MD) simulations of representative proteins from all known folds in explicit water in their native state and along their thermal unfolding pathways. Here we present 188-fold representatives and their native state simulations and analyses. These 188 targets represent 67% of all the structures in the Protein Data Bank. The behavior of several specific targets is highlighted to illustrate general properties in the full dataset and to demonstrate the role of MD in understanding protein function and stability. As an example of what can be learned from mining the Dynameomics database, we identified a protein fold with heightened localized dynamics. In one member of this fold family, the motion affects the exposure of its phosphorylation site and acts as an entropy sink to offset another portion of the protein that is relatively immobile in order to present a consistent interface for protein docking. In another member of this family, a polymorphism in the highly mobile region leads to a host of disease phenotypes. We have constructed a web site to provide access to a novel hybrid relational/multidimensional database (described in the succeeding two papers) to view and interrogate simulations of the top 30 targets: http://www.dynameomics.org. The Dynameomics database, currently the largest collection of protein simulations and protein structures in the world, should also be useful for determining the rules governing protein folding and kinetic stability, which should aid in deciphering genomic information and for protein engineering and design.

Sensitivity of the folding/unfolding transition state ensemble of chymotrypsin inhibitor 2 to changes in temperature and solvent.

To better characterize the transition state for folding/unfolding and its sensitivity to environmental changes, we have run multiple molecular dynamics simulations of chymotrypsin inhibitor 2 (CI2) under varying solvent conditions and temperature. The transition state structures agree well with experiment, and are similar under all of the conditions investigated here. Increasing the temperature leads to some movement in the position of the transition state along several reaction coordinates, as measured by changes in properties of the transition state structures. These structural changes are in the direction of a more native‐like transition state as denaturation conditions become more severe, as expected for a Hammond effect. These structural changes are not, however, reflected in the global structure as measured by the total number of contacts or the average S‐values. These results suggest that the small changes in average Φ‐values with temperature seen by experiment may be due to an increase in the sensitivity of the transition state to mutation rather than a change in the average structure of the transition state. A simple analysis of the rates of unfolding indicates that the free energy barrier to unfolding decreases with increasing temperature, but even in our very high temperature simulations there is a small free energy barrier.

All-Atom Simulations Of Protein Folding And Unfolding

Publisher Summary The chapter focuses on the all-atom simulation of protein folding and unfolding. The pathway and funnel ideas are not mutually exclusive. A pathway view is essentially a subset of the funnel view. It imagines that there are common features of the conformations that a peptide chain assumes as it travels different routes down the funnel. These common features can then be used to describe a pathway by which an unfolded structure finds its way to the native structure. The results of molecular dynamics simulations of protein unfolding suggest a unification of the funnel and pathway views of protein folding. The funnel-shaped free energy surface described by statistical mechanics and simplified protein models is a robust and accurate model for the energy surface of random heteropolymers. Protein refolding simulation is still by far the longest continuous all-atom molecular dynamics simulation published. It is unlikely that it will lose that status in the near future. Additionally, as discussed earlier, truly meaningful data are best obtained from several simulations of the same system. Thus, it is probable that the pathways from these simulations will be biased toward hydrophobic collapse and that the simulations have not been adequately validated by comparison with experimentation. In addition, other fundamental flaws to this approach have been pointed out recently. To do this in a statistically relevant fashion, it is necessary to simulate many examples of the same substructure with different sequences and from proteins with different folds.