Protein conformational flexibility analysis with noisy data.

Protein conformational changes play a critical role in biological functions such as ligand-protein and protein-protein interactions. Due to the noise in structural data, determining salient conformational changes reliably and efficiently is a challenging problem. This paper presents an efficient algorithm for analyzing protein conformational changes, when the data is noisy. It applies a statistical flexibility test to all contiguous fragments of a protein and combines the information from these tests to compute a consensus flexibility measure for each residue of the protein. We tested the algorithm using data from the Protein Data Bank and the Macromolecular Movements Database. The results show that our algorithm can reliably detect different types of salient conformational changes, including well-known examples such as hinge and shear, as well as the flap motion of HIV-1 protease. The software implementing our algorithm is available at http://motion.comp.nus.edu.sg/projects/proflexana/ proflexana.html.