Protein side-chain prediction algorithm using three layer perceptrons

Accurate protein side-chain conformation prediction is crucial for protein structure prediction and protein design methods and a variety of algorithms have been developed for the task however, faster and more accurate methods are still required. We have developed a new prediction method, SIDEpro, which begins by setting the rotamer probabilities for each residue from a backbone dependent rotamer library, then the probabilities are iteratively updated using a three layer perceptron that takes the distances to the surrounding atoms and their types as input. When the updated rotamer probabilities all converge the method returns the most likely rotamer for each residue as the prediction. The resulting models frequently contain steric clashes, thus we developed a procedure to resolve clashes with minimal change to the prediction. SCWRL is widely recognized as the best method for rapid side-chain prediction, and SCWRL4 is the most recent release. SIDEpro was evaluated using the 379 protein test set used to evaluate SCWRL4. A training set of 252 proteins with less than 25% sequence identity to any of the test set proteins was used for training. Using the SCWRL4 test set, SIDEpro accuracy (chi1 85.92%, chi 1+2 74.53%) was slightly better than SCWRL4-FRM (chi1 85.54%, chi 1+2 74.09%) and approximately 5 times faster. SIDEpro was clearly more accurate than SCWRL4-RRM (chi1 84.35%, chi1+2 71.78%) and approximately 2 times faster. In addition, on a test set of several very large protein complexes, SIDEpro is approximately 10 times faster than SCWRL4-FRM and 7 times faster than SCWRL-RRM.