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

Mutations01:39

Mutations

82.1K
Overview
82.1K
RNA Stability01:53

RNA Stability

33.5K
Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
33.5K
Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

10.6K
The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...
10.6K
Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
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...
4.2K
Protein Folding01:25

Protein Folding

8.0K
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...
8.0K
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

6.8K
Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....
6.8K

You might also read

Related Articles

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

Sort by
Same author

A Nomogram for Predicting Successful Weaning from Invasive Mechanical Ventilation Withdrawal in Patients with Chronic Obstructive Pulmonary Disease Complicated by Respiratory Failure.

International journal of chronic obstructive pulmonary disease·2026
Same author

Dual Mechanisms of crRNA 3'-Extension-Mediated Cas12a Attenuation Enable Programmable One-Pot CRISPR Diagnostics.

Analytical chemistry·2026
Same author

A porcine circovirus type 2d-based virus-like particle subunit vaccine effectively protects pigs against homologous challenge.

Frontiers in microbiology·2026
Same author

An approach based on Hilbert transform to extract coherent modes from Doppler backscattering system under imbalances of quadrature mixer.

The Review of scientific instruments·2026
Same author

Active surveillance for low-risk papillary thyroid carcinoma: Integrating guidelines, emerging evidence, and directions.

iScience·2026
Same author

Nomogram with late neurological deterioration as a key predictor for poor functional outcomes after endovascular therapy in acute basilar artery occlusion beyond 24 hours.

Stroke and vascular neurology·2026
Same journal

Structure of Perinereis linea erythrocruorin reveals a compact extracellular globin megacomplex.

Structure (London, England : 1993)·2026
Same journal

Meet the author: Stephen Brohawn.

Structure (London, England : 1993)·2026
Same journal

Tetraspanins bring Norrin into focus: Structural insights into ligand-specific Wnt signaling.

Structure (London, England : 1993)·2026
Same journal

Uncovering subtype-selective activation of the K<sub>Ca</sub>3.1 channel by SKA-111.

Structure (London, England : 1993)·2026
Same journal

Identification and structure determination of a type III-Bv CRISPR complex that post-translationally modifies an associated toxin.

Structure (London, England : 1993)·2026
Same journal

Cryo-EM structure of the Arabidopsisthaliana ribosome in translating and non-translating states.

Structure (London, England : 1993)·2026
See all related articles

Related Experiment Video

Updated: Jun 30, 2025

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

7.3K

PMSPcnn: Predicting protein stability changes upon single point mutations with convolutional neural network.

Xiaohan Sun1, Shuang Yang1, Zhixiang Wu1

  • 1College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.

Structure (London, England : 1993)
|March 20, 2024
PubMed
Summary
This summary is machine-generated.

Predicting protein stability changes from mutations is crucial for understanding genetic diseases. A new convolutional neural network model, PMSPcnn, accurately forecasts these changes, improving disease-related mutation analysis.

More Related Videos

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

1.8K
How to Stabilize Protein: Stability Screens for Thermal Shift Assays and Nano Differential Scanning Fluorimetry in the Virus-X Project
07:22

How to Stabilize Protein: Stability Screens for Thermal Shift Assays and Nano Differential Scanning Fluorimetry in the Virus-X Project

Published on: February 11, 2019

28.2K

Related Experiment Videos

Last Updated: Jun 30, 2025

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

7.3K
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

1.8K
How to Stabilize Protein: Stability Screens for Thermal Shift Assays and Nano Differential Scanning Fluorimetry in the Virus-X Project
07:22

How to Stabilize Protein: Stability Screens for Thermal Shift Assays and Nano Differential Scanning Fluorimetry in the Virus-X Project

Published on: February 11, 2019

28.2K

Area of Science:

  • Computational Biology
  • Biophysics
  • Genetics

Background:

  • Protein missense mutations are significant contributors to human genetic diseases.
  • Accurate prediction of protein stability changes caused by mutations remains a challenge.

Purpose of the Study:

  • To develop an unbiased and effective model for predicting protein stability changes due to single point mutations.
  • To improve the accuracy of predicting stabilizing mutations and mutations with extreme stability changes.

Main Methods:

  • Development of PMSPcnn, a convolutional neural network model.
  • Incorporation of an anti-symmetry property for balanced training data.
  • Utilizing persistent homology for protein structural and topological feature extraction.
  • Implementation of a regression stratification cross-validation scheme.

Main Results:

  • PMSPcnn demonstrates superior performance on three benchmark datasets (Ssym, p53, myoglobin) compared to existing predictors.
  • The model shows improved prediction accuracy, especially for stabilizing mutations.
  • PMSPcnn outperforms current methods in predicting stability changes for membrane proteins.
  • Enhanced prediction for mutations with extreme ΔΔG values.

Conclusions:

  • PMSPcnn is a promising and effective tool for predicting protein stability changes.
  • The model offers advancements in understanding the impact of mutations on protein stability.
  • This method has significant implications for genetic disease research and drug development.