Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....

Protein Organization

Protein Organization

Protein and Protein Structure

Protein and Protein Structure

Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...

Structural Protein Function

Structural Protein Function

Structural Protein Function

Structural Protein Function

Structural proteins are a category of proteins responsible for functions ranging from cell shape and movement to providing support to major structures such as bones, cartilage, hair, and muscles. This group includes proteins such as collagen, actin, myosin, and keratin.
Collagen, the most abundant protein in mammals, is found throughout the body. In connective tissue, such as skin, ligaments, and tendons, it provides tensile strength and elasticity. In bones and teeth, it mineralizes to...

Protein Folding

Protein Folding

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

GraphUnet-SS: A novel deep learning model for protein secondary structure prediction based on U-Net architecture.

Computers in biology and medicine·2026

Same author

An effective colorectal polyp classification for histopathological images based on supervised contrastive learning.

Computers in biology and medicine·2024

Same author

In-Domain Transfer Learning Strategy for Tumor Detection on Brain MRI.

Diagnostics (Basel, Switzerland)·2023

Same author

Developing deep learning methods for classification of teeth in dental panoramic radiography.

Oral surgery, oral medicine, oral pathology and oral radiology·2023

Same author

Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization.

Computer methods and programs in biomedicine·2023

Same author

A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning.

Clinical imaging·2022

Search research articles

Related Experiment Video

Updated: Dec 15, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Structural profile matrices for predicting structural properties of proteins.

Nuh Azginoglu¹, Zafer Aydin², Mete Celik³

¹Department of Computer Engineering, Nevsehir Haci Bektas Veli University, Nevsehir 50300, Turkey.

Journal of Bioinformatics and Computational Biology

|July 11, 2020

Summary

This summary is machine-generated.

New structural profile matrices (SPMs) improve protein 3D structure prediction accuracy. These matrices, derived from various template alignment methods, offer enhanced input for prediction algorithms, boosting performance significantly.

Keywords:

Protein structure prediction secondary structure solvent accessibility structural profile matrix torsion angle

More Related Videos

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

Related Experiment Videos

Last Updated: Dec 15, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

Area of Science:

Computational biology
Structural bioinformatics

Background:

Accurate prediction of protein 3D structure is crucial for understanding biological function.
Existing methods for predicting protein structural properties can be further enhanced.

Purpose of the Study:

To develop novel structural profile matrices (SPMs) for improved protein secondary structure, solvent accessibility, and torsion angle predictions.
To evaluate the efficacy of these SPMs as input for 3D structure prediction algorithms.

Main Methods:

Structural templates were identified using eight alignment methods within the LOMETS server, alongside gap affine alignment, ScanProsite, PfamScan, and HHblits.
Template contributions were weighted based on similarity to the target, assessed via sequence alignment scores.
SPMs were also computed using Homolpro with unweighted BLAST alignments for comparison.

Main Results:

Incorporating the developed SPMs into the DSPRED classifier significantly improved prediction accuracy on two challenging benchmarks.
SPMs generated using threading methods from the LOMETS server yielded the most accurate predictions.
Higher accuracy predictions correlated with increased computational cost for SPM generation.

Conclusions:

Novel structural profile matrices (SPMs) enhance protein property prediction accuracy.
Weighted template contributions and advanced alignment methods (e.g., LOMETS threading) are key to improved performance.
A trade-off exists between prediction accuracy and computational cost.