A protein folding potential that places the native states of a large number of proteins near a local minimum.
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 approximately 4 A rmsd and 71 native conformations within approximately 6 A 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.
Chhajer
Mukesh
M
Department of Chemistry, University of North Carolina, Chapel Hill, NC 27599, USA. mchhajer@email.unc.edu
Crippen
Gordon M
GM
D008958:Models, Molecular; D015394:Molecular Structure; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry; D012997:Solvents / Q000737:chemistry
D011506:Proteins; D012997:Solvents