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Protein Science (2005), 14:1741-1752. Published by Cold Spring Harbor Laboratory Press. Copyright © 2005 The Protein Society
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Lessons from the design of a novel atomic potential for protein folding

William W. Chen1 and Eugene I. Shakhnovich2

1 Department of Biophysics, Harvard University, Boston, Massachusetts 02115, USA
2 Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA

(RECEIVED March 2, 2005; FINAL REVISION March 2, 2005; ACCEPTED April 11, 2005)

We investigate all-atom potentials of mean force for estimating free energies in protein folding and fold recognition. We search through the space potentials and design novel atomic potentials with a random mixing approximation and a contact-correlated Gaussian approximation of decoy states. We show that the two derived potentials are highly correlated, supporting the use of the random energy model as an accurate statistical description of protein conformational states. The novel atomic potentials perform well in a Z-score and fold decoy recognition test. Furthermore, the designed atomic potential performs slightly and significantly better than atomic potentials derived under a quasi-chemical assumption. While accounting for connectivity correlations between atom types does not improve the performance of the designed potential, we show these correlations lead to ambiguities in the distribution of energetic contributions for atoms on the same residue. Within the confines of the model then, many potentials may exist which stabilize all native folds in subtly different ways. Comparison of different protein conformations under the various atomic potentials reveals both a remarkable degree of correspondence in the estimated free energies and a remarkable degree of correspondence in the identity of the contacts types that make the dominant contributions to the estimated free energies. This consistency may be interpreted as a sign that the design procedure is extracting physically meaningful quantities.

Keywords: atomic; potential; protein folding; fold recognition; random energy model; optimization

Article and publication are at http://www.proteinscience.org/cgi/doi/10.1110/ps.051440705.


Reprint requests to: Eugene I. Shakhnovich, Harvard University, Department of Chemistry and Chemical Biology, 12 Oxford St., Cambridge, MA 02138, USA; e-mail: eugene{at}belok.harvard.edu; fax: (617) 495-3075.


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