Dataset Information

Measurement of energy landscape roughness of folded and unfolded proteins.

ABSTRACT: The dynamics of protein conformational changes, from protein folding to smaller changes, such as those involved in ligand binding, are governed by the properties of the conformational energy landscape. Different techniques have been used to follow the motion of a protein over this landscape and thus quantify its properties. However, these techniques often are limited to short timescales and low-energy conformations. Here, we describe a general approach that overcomes these limitations. Starting from a nonnative conformation held by an aromatic disulfide bond, we use time-resolved spectroscopy to observe nonequilibrium backbone dynamics over nine orders of magnitude in time, from picoseconds to milliseconds, after photolysis of the disulfide bond. We find that the reencounter probability of residues that initially are in close contact decreases with time following an unusual power law that persists over the full time range and is independent of the primary sequence. Model simulations show that this power law arises from subdiffusional motion, indicating a wide distribution of trapping times in local minima of the energy landscape, and enable us to quantify the roughness of the energy landscape (4-5 k(B)T). Surprisingly, even under denaturing conditions, the energy landscape remains highly rugged with deep traps (>20 k(B)T) that result from multiple nonnative interactions and are sufficient for trapping on the millisecond timescale. Finally, we suggest that the subdiffusional motion of the protein backbone found here may promote rapid folding of proteins with low contact order by enhancing contact formation between nearby residues.

SUBMITTER: Milanesi L

PROVIDER: S-EPMC3511724 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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Measurement of energy landscape roughness of folded and unfolded proteins.

Milanesi Lilia L Waltho Jonathan P JP Hunter Christopher A CA Shaw Daniel J DJ Beddard Godfrey S GS Reid Gavin D GD Dev Sagarika S Volk Martin M

Proceedings of the National Academy of Sciences of the United States of America 20121112 48

The dynamics of protein conformational changes, from protein folding to smaller changes, such as those involved in ligand binding, are governed by the properties of the conformational energy landscape. Different techniques have been used to follow the motion of a protein over this landscape and thus quantify its properties. However, these techniques often are limited to short timescales and low-energy conformations. Here, we describe a general approach that overcomes these limitations. Starting ...[more]

PMID: 23150572

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Project description:BackgroundStructural excursions of a protein at equilibrium are key to biomolecular recognition and function modulation. Protein modeling research is driven by the need to aid wet laboratories in characterizing equilibrium protein dynamics. In principle, structural excursions of a protein can be directly observed via simulation of its dynamics, but the disparate temporal scales involved in such excursions make this approach computationally impractical. On the other hand, an informative representation of the structure space available to a protein at equilibrium can be obtained efficiently via stochastic optimization, but this approach does not directly yield information on equilibrium dynamics.MethodsWe present here a novel methodology that first builds a multi-dimensional map of the energy landscape that underlies the structure space of a given protein and then queries the computed map for energetically-feasible excursions between structures of interest. An evolutionary algorithm builds such maps with a practical computational budget. Graphical techniques analyze a computed multi-dimensional map and expose interesting features of an energy landscape, such as basins and barriers. A path searching algorithm then queries a nearest-neighbor graph representation of a computed map for energetically-feasible basin-to-basin excursions.ResultsEvaluation is conducted on intrinsically-dynamic proteins of importance in human biology and disease. Visual statistical analysis of the maps of energy landscapes computed by the proposed methodology reveals features already captured in the wet laboratory, as well as new features indicative of interesting, unknown thermodynamically-stable and semi-stable regions of the equilibrium structure space. Comparison of maps and structural excursions computed by the proposed methodology on sequence variants of a protein sheds light on the role of equilibrium structure and dynamics in the sequence-function relationship.ConclusionsApplications show that the proposed methodology is effective at locating basins in complex energy landscapes and computing basin-basin excursions of a protein with a practical computational budget. While the actual temporal scales spanned by a structural excursion cannot be directly obtained due to the foregoing of simulation of dynamics, hypotheses can be formulated regarding the impact of sequence mutations on protein function. These hypotheses are valuable in instigating further research in wet laboratories.

Dataset Information

Measurement of energy landscape roughness of folded and unfolded proteins.

Publications

Measurement of energy landscape roughness of folded and unfolded proteins.

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