Feedback algorithm and web-server for protein structure alignment

We have developed a feedback algorithm for protein structure alignment that uses a series of phases to improve the global alignment between two protein backbones. The method implements a self-improving learning strategy by sending the output of one phase, the global alignment, to the next phase as an input. A web portal implementing this method has been constructed and is freely available for use at http://fpsa.cs.uno.edu/. Based on hundreds of test cases, we compare our algorithm with three other, commonly used methods: CE, Dali, and SSM. Our results show that, in most cases, our algorithm outputs a larger number of aligned positions when the (C_α) RMSD is comparable. Also, in many cases where the number of aligned positions is larger or comparable to the other methods, our learning method is able to achieve a smaller (C _α) RMSD than the other methods tested.