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

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...

You might also read

Related Articles

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

Sort by
Same author

HiGATE: hierarchical graph attention for multi-scale tissue encoder in computational pathology.

Frontiers in oncology·2026
Same author

Upcycling shaddock peel waste into a Fe/Fe<sub>3</sub>C@porous carbon sensor for ultrasensitive electrochemical detection of carbendazim.

Analytica chimica acta·2026
Same author

Stage-specific environmental responses and divergent distributional shifts of Antarctic krill under climate change in the Cosmonaut Sea.

Journal of environmental management·2026
Same author

Meat quality assessment at different slaughter weights of broilers sold in the retail market of Dhaka City, Bangladesh: An integrated approach.

Journal of advanced veterinary and animal research·2026
Same author

Correction: Machine learning-based radiomics approach assessing preoperative non-contrast CT for microsatellite instability prediction in colon cancer.

Frontiers in physiology·2026
Same author

Correction: A two-stage deep learning prediction system for colon cancer microsatellite instability status using CT images.

Frontiers in oncology·2026
Same journal

Anti-mycobacterial activity of phytocompounds from <i>Ricinus communis</i> L. - an integrated <i>in-vitro</i> and <i>in-silico</i> approach.

Journal of biomolecular structure & dynamics·2026
Same journal

Binding studies of the X-ray characterized [SnMe<sub>2</sub>Cl<sub>2</sub>(Me<sub>2</sub>phen)] complex with human serum albumin: experimental and molecular docking approaches.

Journal of biomolecular structure & dynamics·2026
Same journal

Computational design and experimental validation of peptide inhibitors to disrupt urease enzyme maturation in pathogenic bacteria <i>Proteus mirabilis</i>.

Journal of biomolecular structure & dynamics·2026
Same journal

Wavelet-domain multiway spectral separation of free drug, DNA, and drug-DNA complex profiles for quantitative binding analysis based on fractional occupancy (<i>θ</i>).

Journal of biomolecular structure & dynamics·2026
Same journal

Gene expression and microsecond scale conformational dynamics suggest potential regulatory mechanisms for the expanded subtilase family of <i>T. rubrum</i>.

Journal of biomolecular structure & dynamics·2026
Same journal

Deciphering the Role of Sugar Osmolytes in Free and Nano forms to Mitigate Protein Aggregation: Insights from Biophysical and Microscopic Studies.

Journal of biomolecular structure & dynamics·2026
See all related articles

Related Experiment Video

Updated: Jun 4, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Predicting sumoylation site by feature selection method.

YuDong Cai1, JianFeng He, Lin Lu

  • 1Institute of System Biology, Shanghai University, 99 Shangda Road, Shanghai, 200244, China. caiyudong@staff.shu.edu.cn

Journal of Biomolecular Structure & Dynamics
|February 8, 2011
PubMed
Summary
This summary is machine-generated.

Predicting protein sumoylation sites is crucial. This study developed a two-stage method using protein families and amino acid indices, achieving high accuracy for identifying sumoylation sites on proteins.

More Related Videos

Localization of SUMO-modified Proteins Using Fluorescent Sumo-trapping Proteins
06:23

Localization of SUMO-modified Proteins Using Fluorescent Sumo-trapping Proteins

Published on: April 27, 2019

SUMO-Binding Entities (SUBEs) as Tools for the Enrichment, Isolation, Identification, and Characterization of the SUMO Proteome in Liver Cancer
08:29

SUMO-Binding Entities (SUBEs) as Tools for the Enrichment, Isolation, Identification, and Characterization of the SUMO Proteome in Liver Cancer

Published on: November 1, 2019

Related Experiment Videos

Last Updated: Jun 4, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Localization of SUMO-modified Proteins Using Fluorescent Sumo-trapping Proteins
06:23

Localization of SUMO-modified Proteins Using Fluorescent Sumo-trapping Proteins

Published on: April 27, 2019

SUMO-Binding Entities (SUBEs) as Tools for the Enrichment, Isolation, Identification, and Characterization of the SUMO Proteome in Liver Cancer
08:29

SUMO-Binding Entities (SUBEs) as Tools for the Enrichment, Isolation, Identification, and Characterization of the SUMO Proteome in Liver Cancer

Published on: November 1, 2019

Area of Science:

  • Biochemistry
  • Proteomics
  • Bioinformatics

Background:

  • Small ubiquitin-like modifier (SUMO) proteins are crucial for post-translational modification.
  • Protein sumoylation plays a significant role in various cellular processes.
  • Accurate prediction of sumoylation sites is essential for understanding protein function.

Purpose of the Study:

  • To develop and validate a computational method for predicting protein sumoylation sites.
  • To enhance the accuracy of identifying specific sumoylation sites within proteins.

Main Methods:

  • A two-stage prediction strategy was employed.
  • Stage 1: Protein family (PFAM) encoding and Nearest Network Algorithm (NNA) for sumoylation presence prediction.
  • Stage 2: Amino Acid Index encoding of nonapeptides and NNA for specific site prediction.

Main Results:

  • The two-stage method demonstrated high predictive performance.
  • The second-stage predictor achieved 99.55% accuracy with 12 features.
  • A Matthews Correlation Coefficient of 0.7952 was obtained.

Conclusions:

  • The developed method is a promising tool for predicting protein sumoylation sites.
  • The feature selection and algorithmic approach contribute to accurate prediction.
  • The study provides insights into features important for sumoylation site prediction.