Protein conformational changes play a critical role in vital biological functions. Due to noise in data, deteremining salient conformational changes accurately and efficiently is a challenging problem. We have developed an efficient algorithm for analyzing conformational changes of a protein, given its structures in two different conformations. A key element of the algorithm is a statistical test that determines the similarity of two protein structures in the presence of noise. Using data from the Protein Data Bank and the Macromolecular Movements Database, we tested the algorithm on proteins that exhibit a range of different conformational changes. The results show that our algorithm can reliably detect salient conformational changes, including well-known examples such as hinge and shear.
This page provides a web interface for our algorithm. There is also a help page. For theoretical details about this project, please visit this page.