Structural alignment using the generalized Euclidean distance between conformations
نویسندگان
چکیده
The usual Euclidean distance may be generalized to extended objects such as polymers or membranes. Here this distance is used for the first time as a cost function to align structures. We examined the alignment of extended strands to idealized beta-hairpins of various sizes using several cost functions, including RMSD, MRSD, and the minimal distance. We find that using minimal distance as a cost function typically results in an aligned structure which is globally different than that given by an RMSDbased alignment.
منابع مشابه
Minimal distance transformations between links and polymers: principles and examples
The calculation of Euclidean distance between points is generalized to one-dimensional objects such as strings or polymers. Necessary and sufficient conditions for the minimal transformation between two polymer configurations are derived. Transformations consist of piecewise rotations and translations subject to Weierstrass–Erdmann corner conditions. Numerous examples are given for the special ...
متن کاملRemoving car shadows in video images using entropy and Euclidean distance features
Detecting car motion in video frames is one of the key subjects in computer vision society. In recent years, different approaches have been proposed to address this issue. One of the main challenges of developed image processing systems for car detection is their shadows. Car shadows change the appearance of them in a way that they might seem stitched to other neighboring cars. This study aims ...
متن کاملAssessment of the Log-Euclidean Metric Performance in Diffusion Tensor Image Segmentation
Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep impact on Diffusion Tensor Image (DTI) segmentation results. The geodesic metric is the best distance measure since it yields high-quality segmentation results. However, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. The main goal of this ...
متن کاملA generalization of Profile Hidden Markov Model (PHMM) using one-by-one dependency between sequences
The Profile Hidden Markov Model (PHMM) can be poor at capturing dependency between observations because of the statistical assumptions it makes. To overcome this limitation, the dependency between residues in a multiple sequence alignment (MSA) which is the representative of a PHMM can be combined with the PHMM. Based on the fact that sequences appearing in the final MSA are written based on th...
متن کاملPDBFlex: exploring flexibility in protein structures
The PDBFlex database, available freely and with no login requirements at http://pdbflex.org, provides information on flexibility of protein structures as revealed by the analysis of variations between depositions of different structural models of the same protein in the Protein Data Bank (PDB). PDBFlex collects information on all instances of such depositions, identifying them by a 95% sequence...
متن کامل