@article {87106,
	title = {Structural Mining:  Self-Consistent Design on Flexible Protein-Peptide Docking and Transferable Binding Affinity Potential},
	journal = {J. Am. Chem. Soc.},
	volume = {126},
	year = {2004},
	month = {2004},
	pages = {8515 - 8528},
	abstract = {A flexible protein?peptide docking method has been designed to consider not only ligand flexibility but also the flexibility of the protein. The method is based on a Monte Carlo annealing process. Simulations with a distance root-mean-square (dRMS) virtual energy function revealed that the flexibility of protein side chains was as important as ligand flexibility for successful protein?peptide docking. On the basis of mean field theory, a transferable potential was designed to evaluate distance-dependent protein?ligand interactions and atomic solvation energies. The potential parameters were developed using a self-consistent process based on only 10 known complex structures. The effectiveness of each intermediate potential was judged on the basis of a Z score, approximating the gap between the energy of the native complex and the average energy of a decoy set. The Z score was determined using experimentally determined native structures and decoys generated by docking with the intermediate potentials. Using 6600 generated decoys and the Z score optimization criterion proposed in this work, the developed potential yielded an acceptable correlation of R2 = 0.77, with binding free energies determined for known MHC I complexes (Class I Major Histocompatibility protein HLA-A*0201) which were not present in the training set. Test docking on 25 complexes further revealed a significant correlation between energy and dRMS, important for identifying native-like conformations. The near-native structures always belonged to one of the conformational classes with lower predicted binding energy. The lowest energy docked conformations are generally associated with near-native conformations, less than 3.0 {\r A} dRMS (and in many cases less than 1.0 {\r A}) from the experimentally determined structures.},
	url = {http://dx.doi.org/10.1021/ja032018q},
	author = {Liu, Zhijie and Dominy, Brian N. and Eugene I. Shakhnovich}
}
