Abstract

Inherent structure theory is used to discover strong connections between simple characteristics of protein structure and the energy landscape of a Gō model. The potential energies and vibrational free energies of inherent structures are highly correlated, and both reflect simple measures of networks of native contacts. These connections have important consequences for models of protein dynamics and thermodynamics.

Highlights

  • Protein activity is controlled by dynamical transitions among conformational substates1͔; the transitions may be understood in terms of motions on an energy landscape2͔

  • Substates correspond to local minima in the energy landscape, and transitions correspond to the hurdling of barriers between minima

  • Structural-glass-forming liquids have been fruitfully characterized using inherent structureIStheory8,9͔, which treats the energy landscape as a set of discrete basins that are separated by saddles

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Summary

Hidden structure in protein energy landscapes

Inherent structure theory is used to discover strong connections between simple characteristics of protein structure and the energy landscape of a Gō model. The potential energies and vibrational free energies of inherent structures are highly correlated, and both reflect simple measures of networks of native contacts. These connections have important consequences for models of protein dynamics and thermodynamics. Baumketner, Shea, and Hiwatari11͔ have applied IS theory to study the glass transition in a coarse-grained model of a 16-residue polypeptide; by IS analysis of molecular dynamics trajectories, they demonstrated the ability to rigorously calculate the glass transition temperature due to freezing in the native-state basin. The protein exhibited multiple transitions between extended and collapsed states during the course of the simulation, and the inherent structure ensembles exhibited a bimodal probability distribution PISe␣ , T␪͒ of collapsed and extended inherent-structure potential energies e␣ ͑Fig. 2͒, similar to the distribution in Ref. The contribution to Fv from the highest 1/3 of the eigenvalues does not change for

HIDDEN STRUCTURE IN PROTEIN ENERGY LANDSCAPES
There are interesting connections between the structure of
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