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

Creators: Chhajer, Mukesh, Crippen, Gordon M

  • File Type: pdf | Filesize: 341.7 KB
  • Date Added: 2012-09-05
  • Date Created: 2002-08-06

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 &#197; rmsd and 71 native conformations within ~6 &#197; 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.