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

11.8K
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...
11.8K
Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

6.4K
Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
6.4K
Protein Folding01:22

Protein Folding

112.3K
Overview
112.3K
Protein Folding01:25

Protein Folding

8.8K
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...
8.8K
Protein Folding01:22

Protein Folding

29.7K
29.7K
Conservation of Protein Domains02:26

Conservation of Protein Domains

2.9K
2.9K

You might also read

Related Articles

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

Sort by
Same author

Feasibility of 100 kV Low-voltage Bone Mineral Density Measurement with Quantitative CT: Phantom and Clinical Research.

Calcified tissue international·2025
Same author

CT delta-radiomics predicts the risks of blood transfusion and massive bleeding during spinal tumor surgery.

Cancer imaging : the official publication of the International Cancer Imaging Society·2025
Same author

Diagnostic value of dual-energy CT virtual monochromatic imaging for supraspinatus tendon injuries: a comparison with standard CT and MRI.

European radiology·2025
Same author

Deep-learning based multi-modal models for brain age, cognition and amyloid pathology prediction.

Alzheimer's research & therapy·2025
Same author

Improving Deep Learning-Based Grading of Partial-thickness Supraspinatus Tendon Tears with Guided Diffusion Augmentation.

Academic radiology·2025
Same author

[Analysis of four brominated flame retardants in mineral water and instant-noodle-bowl samples by magnetic solid-phase extraction coupled with liquid chromatography using magnetic carbon aerogel as adsorbent].

Se pu = Chinese journal of chromatography·2025

Related Experiment Video

Updated: May 1, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.8K

MuFaDDG: a sequence-based multiscale feature fusion framework for protein stability changes prediction.

Jianting Gong1,2, Pengjia Ma1,2, Zllin Ren3

  • 1Academy of Military Medical Sciences, Beijing, 100850, China.

Bioinformatics (Oxford, England)
|April 30, 2026
PubMed
Summary
This summary is machine-generated.

Predicting protein thermodynamic stability changes (ΔΔG) is crucial for protein engineering and medicine. MuFaDDG, a novel sequence-based method, integrates multiscale feature fusion to enhance prediction accuracy.

More Related Videos

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

70.1K
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

9.6K

Related Experiment Videos

Last Updated: May 1, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.8K
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

70.1K
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

9.6K

Area of Science:

  • Computational Biology
  • Biophysics
  • Protein Engineering

Background:

  • Accurate prediction of protein thermodynamic stability changes upon mutation is vital for protein engineering and medical applications.
  • Existing computational methods have limitations in capturing both local and global features for stability prediction.
  • Developing integrated approaches is necessary to leverage the strengths of diverse feature extraction strategies.

Purpose of the Study:

  • To introduce MuFaDDG, a novel sequence-based computational method for predicting protein thermodynamic stability changes (ΔΔG).
  • To integrate multiscale feature fusion for improved accuracy in predicting the impact of single-point mutations on protein stability.
  • To address the limitations of existing methods by combining local and global feature extraction.

Main Methods:

  • MuFaDDG employs a sequence-based approach integrating multiscale feature fusion.
  • The method leverages both local-level and global-level features for enhanced prediction.
  • Specific details of the feature fusion strategy are implemented within the MuFaDDG framework.

Main Results:

  • MuFaDDG demonstrates comparable performance on the S669 benchmark, excelling in predicting stabilizing mutations.
  • The method achieves significant advantages in the ACC metric on the CAGI5 Challenge Frataxin dataset (0.75, 0.88, 0.81).
  • MuFaDDG outperforms leading sequence-based methods (THPLM, DDGemb, DDGun, INPS-Seq) on Myoglobin and shows superior PCC and ACC on the uncurated ThreeFoil protein.

Conclusions:

  • MuFaDDG offers an improved sequence-based approach for predicting protein stability changes (ΔΔG).
  • The integration of multiscale features enhances predictive performance, particularly for stabilizing mutations.
  • The method's strong performance across various benchmarks highlights its potential utility in protein engineering and medicine.