Correlation between knowledge-based and detailed atomic potentials: Application to the unfolding of the GCN4 leucine zipper

Citation
D. Mohanty et al., Correlation between knowledge-based and detailed atomic potentials: Application to the unfolding of the GCN4 leucine zipper, PROTEINS, 35(4), 1999, pp. 447-452
Citations number
48
Categorie Soggetti
Biochemistry & Biophysics
Journal title
PROTEINS-STRUCTURE FUNCTION AND GENETICS
ISSN journal
08873585 → ACNP
Volume
35
Issue
4
Year of publication
1999
Pages
447 - 452
Database
ISI
SICI code
0887-3585(19990601)35:4<447:CBKADA>2.0.ZU;2-1
Abstract
The relationship between the unfolding pseudo free energies of reduced and detailed atomic models of the GCN4 leucine zipper is examined. Starting fro m the native crystal structure, a large number of conformations ranging fro m folded to unfolded were generated by all-atom molecular dynamics unfoldin g simulations in an aqueous environment at elevated temperatures. For the d etailed atomic model, the pseudo free energies are obtained by combining th e CHARMM all-atom potential with a solvation component from the generalized Born, surface accessibility, GB/SA, model. Reduced model energies were eva luated using a knowledge-based potential. Both energies are highly correlat ed. In addition, both show a good correlation with the root mean square dev iation, RMSD, of the backbone from native. These results suggest that knowl edge-based potentials are capable of describing at least some of the proper ties of the folded as well as the unfolded states of proteins, even though they are derived from a database of native protein structures. Since only c onformations generated from an unfolding simulation are used, we cannot ass ess whether these potentials can discriminate the native conformation from the manifold of alternative, low-energy misfolded states. Nevertheless, the se results also have significant implications for the development of a meth odology for multiscale modeling of proteins that combines reduced and detai led atomic models. Proteins 1999;35:447-452, (C) 1999 Wiley-Liss, Inc.