A structure-based method for derivation of all-atom potentials for protein folding

T he dark mystery of protein folding has been greatly illuminated by the last decade's work. This enlightenment has come from the simultaneous flowering of new theoretical approaches (1-3), powerful computational studies (4,5), and a fresh wave of experiments using protein engineering (6) and ultrafast kinetics (7,8). How a disordered chain molecule finds its organized, folded state is no longer a paradox, but a scientific problem requiring a close comparison of theories, computation and experiments. A beautiful experimental study of the mechanism of folding of the B domain of streptococcal protein A appears in this issue of PNAS (9). This study joins such landmarks as the elucidation of the folding mechanism of CI2 and barnase by the same group (10). So what's the news? The excitement comes because this protein has been the poster child of computational folders. It is attractive to computationalists because of its small size, 60 residues, at the extreme limit exhibiting cooperative protein-like thermodynamics. The protein also folds fast, so computer studies have the best chance of success. Numerous simulations were carried out (11-23) without extensive laboratory kinetic studies at the residue level to influence the work. It is thus interesting to see how well the computationalists have been able to predict the folding mechanism without much biasing data. Sato et al. (9) liken the comparison of simulations with their kinetic experiment to the biennial exercise Critical Assessment of Structure Prediction (CASP) (24). They, like most participants in CASP, refer to it as a competition, although the organizers decry that appellation. As the leader of a participating group, I can testify to CASP's painfulness, but, despite its undignified similarity to a sporting event, good science comes from CASP. Likewise, the present results do indeed provoke serious thought.When compared with the old view of a single obligate folding pathway (25), the computational studies are in remarkable agreement with each other and with experiment. All these studies show a diffuse folding mechanism in which a fairly diverse ensemble of structures is guided to the native structure by trading stabilization free energy for configurational entropy (1). The energy landscape resembles a funnel in which more native-like structures are stabilized over kinetic traps that could arise from conflicting energetic signals (''frustration''). In a funnel landscape, although trapping is not a problem, a kinetic bottleneck arises because stabilization energy and entropy do not smoothly compensate each other as the protein descends in the funnel. The ensemble of structures at the bottleneck, called the transition state ensemble (TSE), is probed by examining the effect of changing individual amino acids on folding rates. In a funnel-like landscape, these changes can be converted to values that measure how much more structures in the TSE resemble the native structure or the denatured ensemble. If ϭ 1 for a given residue, in the TSE that residue will be in a ...

Section: Globally Good Predictionsmentioning

confidence: 55%

Section: Devilish Detailsmentioning

confidence: 99%

mentioning

confidence: 99%

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Latest folding game results: Protein A barely frustrates computationalists

Wolynes

2004

“…14 and 29). It is important to note that the move set used in these simulations, although extensively validated (11,12,14,(30)(31)(32), is nonetheless a MC move set and thus lacks the temporal resolution to make exquisitely detailed statements regarding dynamics. As such we confine our dynamical analysis to consider only very coarse-grained features of the folding trajectories.…”

Section: Resultsmentioning

confidence: 99%

Understanding ensemble protein folding at atomic detail

Hubner

Deeds

Shakhnovich

2006

Self Cite

It has long been known that a protein's amino acid sequence dictates its native structure. However, despite significant recent advances, an ensemble description of how a protein achieves its native conformation from random coil under physiologically relevant conditions remains incomplete. Here we present a detailed all-atom model with a transferable potential that is capable of ab initio folding of entire protein domains using only sequence information. The computational efficiency of this model allows us to perform thousands of microsecond-time scale-folding simulations of the engrailed homeodomain and to observe thousands of complete independent folding events. We apply a graph-theoretic analysis to this massive data set to elucidate which intermediates and intermediary states are common to many trajectories and thus important for the folding process. This method provides an atomically detailed and complete picture of a folding pathway at the ensemble level. The approach that we describe is quite general and could be used to study the folding of proteins on time scales orders of magnitude longer than currently possible.engrailed homeodomain ͉ folding pathway ͉ graph theory ͉ Monte Carlo ͉ protein folding O ne of the longest-standing goals of computational biophysics is the creation of a model for protein folding that is both predictive of protein structure and folding mechanism at the atomic level. Despite numerous advances in recent years (1-5), no method has yet been able to follow the folding of an entire protein domain from random coil to its native state over realistic time scales using an atomically detailed representation and a fully transferable potential. Significant progress has been made on the computational prediction of native-state structures for many proteins (6), but such algorithms do not use a single realistic representation of the polypeptide chain and its dynamics from start to finish and as such cannot shed light on the mechanistic details of the folding process. For instance, the highly successful structure prediction ROSETTA algorithm (6) uses a C-␤ representation of the protein for many of its early calculations and is based on dynamics that move entire segments of the chain to instantly adopt complete structural motifs drawn from a database to search conformational space efficiently.Attempts to access the important features of the physical folding process using explicit approximations of physical forces and molecular dynamics simulation protocols have encountered significant barriers in computational efficiency (7). Individual simulations using such protocols are currently limited to tens to hundreds of nanosecond time scales, and although rare fastfolding events can be observed in such simulations (7), these methods cannot access folding events or intermediates that occur on longer time scales (7). Given that even the fastest-folding protein domains fold on the order of tens of microseconds, much of this work has thus focused on protein fragments or designed peptide sequences (7) that...

“…Numerous simulations have been made by using various techniques, including offlattice, all-atom molecular dynamics, and conformational sampling methods (8,(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37). The suggested folding mechanisms range from diffusion-collision to hydrophobic collapse models, and the predictions differ in the order of events on the folding pathway.…”

Section: Discussionmentioning

confidence: 99%

Testing protein-folding simulations by experiment: B domain of protein A

Sato

Religa

Daggett

et al. 2004

135

262

We have assessed the published predictions of the pathway of folding of the B domain of protein A, the pathway most studied by computer simulation. We analyzed the transition state for folding of the three-helix bundle protein, by using experimental ⌽ values on some 70 suitable mutants. Surprisingly, the third helix, which has the most stable ␣-helical structure as a peptide fragment, is poorly formed in the transition state, especially at its C terminus. The protein folds around a nearly fully formed central helix, which is stabilized by extensive hydrophobic side chain interactions. The turn connecting the poorly structured first helix to the central helix is unstructured, but the turn connecting the central helix to the third is in the process of being formed as the N-terminal region of the third helix begins to coalesce. The transition state is inconsistent with a classical framework mechanism and is closer to nucleation-condensation. None of the published atomistic simulations are fully consistent with the experimental picture although many capture important features. There is a continuing need for combining simulation with experiment to describe folding pathways, and of continued testing to improve predictive methods.