A novel high resolution Calpha--Calpha distance dependent force field based on a high quality decoy set.
This work presents a novel C(alpha)--C(alpha) distance dependent force field which is successful in selecting native structures from an ensemble of high resolution near-native conformers. An enhanced and diverse protein set, along with an improved decoy generation technique, contributes to the effectiveness of this potential. High quality decoys were generated for 1489 nonhomologous proteins and used to train an optimization based linear programming formulation. The goal in developing a set of high resolution decoys was to develop a simple, distance-dependent force field that yields the native structure as the lowest energy structure and assigns higher energies to decoy structures that are quite similar as well as those that are less similar. The model also includes a set of physical constraints that were based on experimentally observed physical behavior of the amino acids. The force field was tested on two sets of test decoys not in the training set and was found to excel on all the metrics that are widely used to measure the effectiveness of a force field. The high resolution force field was successful in correctly identifying 113 native structures out of 150 test cases and the average rank obtained for this test was 1.87. All the high resolution structures (training and testing) used for this work are available online and can be downloaded from http://titan.princeton.edu/HRDecoys.
Rajgaria
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Department of Chemical Engineering, Princeton University, Princeton, New Jersey 08544-5263, USA.
McAllister
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SR
Floudas
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CA
D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry; D002244:Carbon / Q000737:chemistry; D003198:Computer Simulation; D030562:Databases, Protein; D057927:Hydrophobic and Hydrophilic Interactions; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry
D000596:Amino Acids; D011506:Proteins; D002244:Carbon