Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
Protein Folding01:22

Protein Folding

Overview
Protein Folding01:22

Protein Folding

Overview
Protein Folding01:25

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Conservation of Protein Domains02:26

Conservation of Protein Domains

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...

You might also read

Related Articles

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

Sort by
Same author

BindRNAgen: Protein-binding RNA sequence generation using latent diffusion models.

Journal of molecular biology·2026
Same author

DrugDL: dual-modal deep learning framework for multi-property drug prediction and targeted therapy discovery.

Bioinformatics (Oxford, England)·2026
Same author

Reconstructing cell-cell interaction network in single-cell spatial transcriptomics via directed heterogeneous graph autoencoder.

Bioinformatics (Oxford, England)·2026
Same author

SMENET: A Multi-View Semantic Model for Multi-Level Enzyme Function Prediction.

IEEE transactions on computational biology and bioinformatics·2025
Same author

Ab-initio amino acid sequence design from protein text description with ProtDAT.

Nature communications·2025
Same author

Simultaneously infer cell pseudotime, velocity field, and gene interaction from multi-branch scRNA-seq data with scPN.

NAR genomics and bioinformatics·2025

Related Experiment Video

Updated: Jun 28, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Predicting protein fold pattern with functional domain and sequential evolution information.

Hong-Bin Shen1, Kuo-Chen Chou

  • 1Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, 800 Dongchuan Road, Shanghai 200240, China. hbshen@sjtu.edu.cn

Journal of Theoretical Biology
|November 11, 2008
PubMed
Summary
This summary is machine-generated.

Predicting protein fold patterns is challenging. A new method, PFP-FunDSeqE, combines functional and evolutionary data to achieve over 70% accuracy, a first in the field.

More Related Videos

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

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: Jun 28, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

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:

  • Protein bioinformatics
  • Structural biology
  • Computational biology

Background:

  • Protein fold pattern prediction is complex, exceeding standard structural classification.
  • Existing methods struggle, with success rates below 70%.

Purpose of the Study:

  • To develop a novel predictor for identifying protein fold patterns.
  • To improve prediction accuracy beyond current limitations.

Main Methods:

  • A fusion ensemble classifier integrating functional domain and sequential evolution information.
  • Development of the PFP-FunDSeqE predictor.
  • Testing on a benchmark dataset for 27 protein fold patterns.

Main Results:

  • The PFP-FunDSeqE predictor achieved over 70% success rate for protein fold pattern identification.
  • This represents a significant improvement compared to existing predictors on the same dataset.
  • The predictor is available as a public web server.

Conclusions:

  • The novel approach combining functional and evolutionary data significantly enhances protein fold pattern prediction accuracy.
  • PFP-FunDSeqE sets a new benchmark, surpassing the 70% success rate threshold.
  • The publicly accessible web server facilitates further research and application.