MOTIVATION: The biological function of proteins is associated with a variety of motions, ranging from global domain motion to local motion of side chain. We propose a method, dihedral transition analysis (DTA), to identify significant dihedral angle changes between two distinct protein conformations and for characterization of the effect of these transitions on both local and global conformation. RESULTS: Applying DTA to a comprehensive and non-redundant dataset of 459 high-resolution pairs of protein structures, we found that a dihedral transition occurs in 82% of proteins. Multiple dihedral transitions are shown to occur cooperatively along the sequence, which allows us to separate a polypeptide chain into fragments with and without transitions, namely transition fragments (TFs) and stable fragments (SFs), respectively. By characterizing the magnitude of TF conformational change and the effect of the transition on the neighboring fragments, flap and hinge motions are identified as typical motions. DTA is also useful to detect protein motions, subtle in RMSD but significant in terms of dihedral angle changes, such as the peptide-plane flip, the side-chain flip and path-preserving motions. We conclude that DTA is a useful tool to extract potential functional motions, some of which might have been missed using conventional methods for protein motion analysis. AVAILABILITY: http://dynamics.iam.u-tokyo.ac.jp/DTA/

MOTIVATION: To efficiently analyze the 'native ensemble of conformations' accessible to proteins near their folded state and to extract essential information from observed distributions of conformations, reliable mathematical methods and computational tools are needed. RESULT: Examination of 24 pairs of structures determined by both NMR and X-ray reveals that the differences in the dynamics of the same protein resolved by the two techniques can be tracked to the most robust low frequency modes elucidated by principal component analysis (PCA) of NMR models. The active sites of enzymes are found to be highly constrained in these PCA modes. Furthermore, the residues predicted to be highly immobile are shown to be evolutionarily conserved, lending support to a PCA-based identification of potential functional sites. An online tool, PCA_NEST, is designed to derive the principal modes of conformational changes from structural ensembles resolved by experiments or generated by computations. AVAILABILITY: http://ignm.ccbb.pitt.edu/oPCA_Online.htm

Bioinformatics 25(5), 606–614