TITLE

A protein folding potential that places the native states of a large number of proteins near a local minimum

AUTHOR(S)
Chhajer, Mukesh; Crippen, Gordon M.
PUB. DATE
January 2002
SOURCE
BMC Structural Biology;2002, Vol. 2, p4
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Background: We present a simple method to train a potential function for the protein folding problem which, even though trained using a small number of proteins, is able to place a significantly large number of native conformations near a local minimum. The training relies on generating decoys by energy minimization of the native conformations using the current potential and using a physically meaningful objective function (derivative of energy with respect to torsion angles at the native conformation) during the quadratic programming to place the native conformation near a local minimum. Results: We also compare the performance of three different types of energy functions and find that while the pairwise energy function is trainable, a solvation energy function by itself is untrainable if decoys are generated by minimizing the current potential starting at the native conformation. The best results are obtained when a pairwise interaction energy function is used with solvation energy function. Conclusions: We are able to train a potential function using six proteins which places a total of 42 native conformations within ~4 Ã… rmsd and 71 native conformations within ~6 Ã… rmsd of a local minimum out of a total of 91 proteins. Furthermore, the threading test using the same 91 proteins ranks 89 native conformations to be first and the other two as second.
ACCESSION #
29323530

 

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