Semi‐isometric Registration of Line Features for Flexible Fitting of Protein Structures

2015

Vis Comput

We present an algorithm for matching two sets of line segments in 3D that have undergone non-rigid deformations. This problem is motivated by a biology application that seeks a correspondence between the alpha-helices from two proteins, so that matching helices have similar lengths and these can be aligned by some low-distortion deformation. While matching between two feature sets have been extensively studied, particularly for point features, matching line segments has received little attention so far. As typical in point-matching methods, we formulate a graph matching problem and solve it using continuous relaxation. We make two technical contributions. First, we propose a graph construction for undirected line segments such that the optimal matching between two graphs represents an as-rigidas-possible deformation between the two sets of segments. Second, we propose a novel heuristic for discretizing the continuous solution in graph matching. Our heuristic can be applied to matching problems (such as ours) that are not amenable to certain heuristics, and it produces better solutions than those applicable heuristics. Our method is compared with a state-of-art method motivated by the same biological application and demonstrates improved accuracy.

Section: Related Workmentioning

confidence: 93%

Section: Setting Up the Graphmentioning

confidence: 99%

Section: Defining the Affinitiesmentioning

confidence: 99%

Section: Defining the Affinitiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Graph-based deformable matching of 3D line with application in protein fitting

Dou

2015

Vis Comput

Computational Methods for Interpretation of EM Maps at Subnanometer Resolution

Encyclopedia of Life Sciences

Yao

2012

Driven by a remarkable number of technological advances in recent years, electron cryo‐microscopy (cryo‐EM) has played an increasingly important role in deciphering macromolecular structure and function. Today, cryo‐EM routinely achieves subnanometer resolutions, with current state‐of‐the‐art reconstructions approaching atomic resolutions. Though achieving high‐resolution density maps is still a challenging aspect of cryo‐EM, it is possible to isolate individual subunits, identify secondary structures elements and accurately fit atomic models in reconstructions of large macromolecular assemblies. Additionally, computational modelling and feature recognition tools are routinely employed to construct backbone and atomic models of entire assemblies directly from a density map. Together, these tools provide researchers with unprecedented insight into structure and function, revealing everything from subunit arrangements to complex sets of interactions in macromolecular assemblies. Key Concepts: Cryo‐EM is capable of imaging large macromolecular assemblies in order to understand their structure and function. Analysing macromolecular assemblies requires a variety of complex computational tools. In subnanometer resolution cryo‐EM density maps, it is possible to see individual protein subunits, as well as higher‐resolution structural features. It is now possible to construct backbone and atomic models directly from cryo‐EM density maps at near‐atomic resolutions.

Gorgon and pathwalking: Macromolecular modeling tools for subnanometer resolution density maps

Hryc

et al. 2012

Biopolymers

The complex interplay of proteins and other molecules, often in the form of large transitory assemblies, are critical to cellular function. Today, X-ray crystallography and electron cryo-microscopy (cryo-EM) are routinely used to image these macromolecular complexes, though often at limited resolutions. Despite the rapidly growing number of macromolecular structures, few tools exist for modeling and annotating structures in the range of 3-10Å resolution. To address this need, we have developed a number of utilities specifically targeting subnanometer resolution density maps. As part of the 2010 Cryo-EM Modeling Challenge, we demonstrated two of our latest de novo modeling tools, Pathwalking and Gorgon, as well as a tool for secondary structure identification (SSEHunter) and a new rigid-body/flexible fitting tool in Gorgon. In total, we submitted 30 structural models from ten different subnanometer resolution data sets in four of the six challenge categories. Each of our utlities produced accurate structural models and annotations across the various density maps. In the end, the utilities that we present here offer users a robust toolkit for analyzing and modeling protein structure in macromolecular assemblies at non-atomic resolutions.