A protein folding potential that places the native states of a large number of proteins near a local minimum
✍ Scribed by Mukesh Chhajer; Gordon M Crippen
- Publisher
- BioMed Central
- Year
- 2002
- Tongue
- English
- Weight
- 312 KB
- Volume
- 2
- Category
- Article
- ISSN
- 1472-6807
No coin nor oath required. For personal study only.
✦ Synopsis
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.