(The RMSD for this Dali superposition is 3.2 Å.) Buttons below show 50-residue segments of the query ( FtsZ) and backbone for target ( tubulin) where the target α carbons are within 3.5 Å. Because the superposition is about 300 residues long (and the protein chains are longer), it is hard to see details of this superposition in the complexity.This scene is available in Dali except that the target color has been changed to make it more distinct from the red query. The non-superposed segments are white in the query ( FtsZ) and thin in the target ( tubulin).Sequence identity in the superposed regions is about 13%. The example at right shows the bacterial cell division protein FtsZ ( 1fsz:A) superposed by Dali with mammalian tubulin ( 1tub:A). Structure superpositions are usually visualized as the superposed backbone traces of the models. One of these is the global distance test total score, or GDT_TS. When the models being compared have substantial differences, and especially if they have multiple domains, more tolerant estimates of the closenss of fit have been employed, notably in CASP. Z-scores less than 2 are considered to lack statistical significance. The z-score is the distance, in standard deviations, between the observed superposition RMSD and the mean RMSD for random pairs of the same length, with the same or fewer gaps. The statistical significance of a structure superposition, relative to a superposition of random sequence-nonredundant structures in the PDB, is usually measured with a z-score. Deviations can be much larger for models determined by NMR. Crystallographic models of proteins with about 50% sequence identity differ by about 1 Å RMSD. To provide a frame of reference for RMSD values, note that up to 0.5 Å RMSD of alpha carbons occurs in independent determinations of the same protein. The structural differences between two optimally superposed models are usually measured as the Root Mean Square Deviation ( RMSD) between the superposed alpha-carbon positions (excluding deviations from the non-superposed positions). 6.2.3 DeepView = Swiss-PDBViewer example.3.3.1 Multiple chains in each of two models.3.3 Multiple chain structure superposition.Hasegawa and Holm reviewed structure superposition methods in 2009. Wikipedia offers a list of structure superposition software packages and an overview of structure superposition. Some servers (notably Dali, FATCAT, VAST and TopSearch) enable you to upload one 3D model (or specify one in the PDB) and generate a list of the closest structures in the PDB, based on pairwise structure superpositions between your query structure versus each structure in the PDB. All servers listed below enable you to upload two 3D models (or specify them from the PDB) and generate a structure superposition. There are two common applications of structure superposition servers: Characteristics of structure superposition servers and software packages are listed, along with results of testing with a few examples. The purpose of this article is to help in choosing a server or software package for performing structure superposition. When the models superpose closely, it suggests evolutionary and functional relationships that may not be discernable from sequence comparisions. In the case of proteins, structure superposition is often performed without reference to the sequences of the proteins. It is sometimes called structure alignment, but that term is easily confused with a sequence alignment guided by a structure superposition. Structure superposition refers to the optimal superposition, yielding the closest fit in three dimensions, between two or more molecular models. Jump to: navigation, search proteopedia link proteopedia link
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