Helical Indexing
Helical Indexing - Related Videos
12:38
Structure of HIV-1 Capsid Assemblies by Cryo-electron Microscopy and Iterative Helical Real-space Reconstruction
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Cited by 8 •
2011
This article describes a method to obtain a three-dimensional (3D) structure of helically assembled molecules using cryo-electron microscopy. In this protocol, we use HIV-1 capsid assemblies to illustrate the detailed 3D reconstruction procedure for achieving a density map by the iterative helical real-space reconstruction method.
12:24
Helical Organization of Blood Coagulation Factor VIII on Lipid Nanotubes
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Cited by 9 •
2014
We present a combination of Cryo-electron microscopy, lipid nanotechnology, and structure analysis applied to resolve the membrane-bound structure of two highly homologous FVIII forms: human and porcine. The methodology developed in our laboratory to helically organize the two functional recombinant FVIII forms on negatively charged lipid nanotubes (LNT) is described.
09:22
Self-assembling Morphologies Obtained from Helical Polycarbodiimide Copolymers and Their Triazole Derivatives
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2017
Here, we present a protocol to prepare and visualize secondary structures (e.g., fibers, toroidal architectures, and nano-spheres) derived from helical polycarbodiimides. The morphology characterized by both atomic force microscopy (AFM) and scanning electron microscopy (SEM) was shown to depend on molecular structure, concentration, and the solvent of choice.
07:58
Improving the Combustion Performance of a Hybrid Rocket Engine using a Novel Fuel Grain with a Nested Helical Structure
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Cited by 4 •
2021
A technique utilizing a solid fuel grain with a novel nested helical structure to improve the combustion performance of a hybrid rocket engine is presented.
11:09
Constructing Thioether/Vinyl Sulfide-tethered Helical Peptides Via Photo-induced Thiol-ene/yne Hydrothiolation
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Cited by 3 •
2018
We present a protocol for the construction of thioether/vinyl sulfide-tethered helical peptides using photo-induced thiol-ene/thiol-yne hydrothiolation.
FAQs
Axial rise specifies the distance between repeating structural units along the specimen’s axis, while rotational twist describes how each unit turns relative to the next. Together, these parameters define the helical geometry used during computational reconstruction. If either value is assigned incorrectly, structural features may appear misaligned, reducing the reliability of the resulting three-dimensional map.
Layer lines in a diffraction pattern or microscopy image provide evidence of periodic organization within a helical specimen. Their spacing and arrangement help investigators assign the repeat of the structure and estimate its axial and rotational parameters. This analysis connects visible or measured pattern features with the geometry required for subsequent reconstruction rather than treating the specimen as an unstructured filament.
Accurate indexing establishes the repeating geometry used to organize image data during reconstruction. Correct assignments help structural features occupy consistent positions across the calculated map, supporting clearer interpretation of protein assemblies and their interfaces. In infection research, this matters because architectural differences may relate to host recognition, attachment, or replication, and indexing errors can obscure those relationships.
The input differs, but both approaches are used to identify repeating helical geometry. Diffraction patterns emphasize periodic signals, whereas microscopy images provide visual information from the specimen itself. In either case, the analysis seeks helical repeats and parameters such as axial rise and rotational twist. The selected data source therefore influences how structural evidence is recognized before reconstruction.
A typical workflow begins with a diffraction pattern or microscopy image containing an ordered helical specimen. The investigator identifies repeating features or layer lines, assigns the helical repeat, and estimates axial rise and rotational twist. Those parameters are then supplied to computational reconstruction procedures, where they guide the organization of the data and the interpretation of the resulting three-dimensional architecture.
Helical indexing is useful when researchers examine ordered structures that contribute to pathogen biology or host interaction. Relevant examples include filamentous viruses, bacterial pili, and other protein assemblies involved in recognition, attachment, or replication. By improving the structural basis for reconstruction, the method helps relate molecular organization to infection mechanisms and to the way pathogens interact with immune systems.