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The Structure of Intermediate Filaments

The Structure of Intermediate Filaments

The intermediate filaments are one of three widely studied cytoskeletal filaments. They are so named as their diameter (10 nm) is in between that of microfilaments (7 nm) and the microtubules (25 nm). These filaments are highly stable and can remain intact when exposed to high salt concentrations and detergents. These filaments are responsible for providing stability and mechanical support to the cells. They also help in cell adhesion and maintaining tissue integrity.
Intermediate...

RNA Structure

RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...

RNA Structure

RNA Structure

The basic structure of RNA consists of a string of ribonucleotides attached by phosphodiester bonds. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA) involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three...

Chromatin Structure and RNA Splicing

Chromatin Structure and RNA Splicing

Disassembly of Intermediate Filaments

Disassembly of Intermediate Filaments

Intermediate filaments (IFs) do not undergo spontaneous disassembly. Enzymes, kinases, and phosphatases add and remove phosphates from specific sites to regulate their disassembly. The IF concentration in the cytoplasm also regulates the disassembly. If the concentration crosses a threshold, it activates the protein kinases in the vicinity, allowing the phosphorylation of IFs.
Keratin proteins, found at the cell periphery near cell junctions, undergo a cycle of assembly and disassembly. In Type...

Types of Intermediate Filaments

Types of Intermediate Filaments

The intermediate filaments are an essential component of the cytoskeleton. Presently six types of intermediate filament have been identified. Type I and II are acidic and basic keratin proteins. Type III is of mesodermal origin and comprises four proteins: vimentin, desmin, glial fibrillary acidic protein (GFAP), and peripherin. Vimentin is commonly found in mesenchymal cells, desmin in muscle cells, GFAP in astrocytes, while peripherin is found in peripheral nervous system neurons (PNS). Type...

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Related Experiment Video

Updated: Jan 23, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Quality assessment of RNA 3D structure models using deep learning and intermediate 2D maps.

Xiaocheng Liu¹, Wenkai Wang², Zongyang Du^3,4

¹MOE Frontiers Science Center for Nonlinear Expectations, State Key Laboratory of Cryptography and Digital Economy Security, Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, China.

Communications Biology

|January 21, 2026

Summary

RNArank is a new deep learning tool for assessing RNA 3D structure models. It accurately predicts local and global quality, outperforming existing methods and aiding RNA structure research.

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Area of Science:

Computational Biology
Structural Biology
Bioinformatics

Background:

Accurate quality assessment of RNA 3D structures is crucial for computational prediction and design.
Existing methods for RNA structure quality assessment face significant challenges.

Purpose of the Study:

To introduce RNArank, a novel deep learning-based approach for local and global quality assessment of predicted RNA 3D structure models.
To evaluate RNArank's performance against traditional and other deep learning methods.

Main Methods:

RNArank utilizes a Y-shaped residual neural network to process multi-modal features extracted from RNA 3D structure models.
The network predicts inter-nucleotide contact maps and distance deviation maps to estimate local and global accuracy.

Main Results:

RNArank consistently outperforms traditional and other deep learning-based methods in benchmark tests.
The tool shows promising performance in identifying high-quality models for recent CASP targets (CASP15 and CASP16).

Conclusions:

RNArank offers a reliable method for RNA 3D structure quality assessment.
The tool is expected to enhance the reliability of RNA structure modeling and contribute to understanding RNA function.