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

5.3K
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...
5.3K
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.9K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
14.9K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

14.9K
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...
14.9K
Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

15.7K
Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
15.7K

You might also read

Related Articles

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

Sort by
Same author

Genome-wide identification of SNPs in microRNA genes and the SNP effects on microRNA target binding and biogenesis.

Human mutation·2011
Same author

A case of intimal sarcoma of the pulmonary artery successfully treated with chemotherapy.

International journal of clinical oncology·2011
Same author

Exome sequencing identifies frequent mutation of ARID1A in molecular subtypes of gastric cancer.

Nature genetics·2011
Same author

Energetic salts based on dipicrylamine and its amino derivative.

Chemistry (Weinheim an der Bergstrasse, Germany)·2011
Same author

Biophysical properties of slow potassium channels in human embryonic stem cell derived cardiomyocytes implicate subunit stoichiometry.

The Journal of physiology·2011
Same author

Natural variation of folate content and composition in spinach (Spinacia oleracea) germplasm.

Journal of agricultural and food chemistry·2011

Related Experiment Video

Updated: Mar 16, 2026

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

7.8K

Sorting protein decoys by machine-learning-to-rank.

Xiaoyang Jing1, Kai Wang2, Ruqian Lu1

  • 1School of Computer Science, Fudan University, Shanghai 200433, People's Republic of China.

Scientific Reports
|August 18, 2016
PubMed
Summary

New protein structure prediction quality estimation methods, MQAPRank and Quasi-MQAPRank, improve accuracy. Quasi-MQAPRank shows enhanced performance on benchmark datasets, advancing computational biology.

More Related Videos

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

4.1K
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

2.7K

Related Experiment Videos

Last Updated: Mar 16, 2026

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

7.8K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

4.1K
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

2.7K

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Machine Learning in Biology

Background:

  • Protein structure prediction is crucial for understanding biological functions.
  • Accurate quality estimation of predicted protein models is essential for reliable downstream applications.
  • Existing quality estimation methods fall into single-model, clustering-based, and quasi single-model categories.

Purpose of the Study:

  • To develop novel single-model and quasi single-model methods for protein structure prediction quality estimation.
  • To benchmark the performance of the proposed methods against existing approaches.
  • To enhance the accuracy and reliability of protein model quality assessment.

Main Methods:

  • Development of MQAPRank, a single-model quality estimation method based on the learning-to-rank algorithm.
  • Implementation of Quasi-MQAPRank, a quasi single-model method building upon MQAPRank.
  • Benchmarking on the 3DRobot and CASP11 datasets using five-fold cross-validation.

Main Results:

  • MQAPRank outperformed other single-model methods when their outputs were used as features.
  • The quasi single-model method, Quasi-MQAPRank, further improved prediction accuracy.
  • Both methods demonstrated competitive performance on the CASP11 dataset, with Quasi-MQAPRank excelling on the CASP11 Best150 subset.

Conclusions:

  • The proposed MQAPRank and Quasi-MQAPRank methods represent significant advancements in protein structure prediction quality estimation.
  • Quasi-MQAPRank offers a robust approach for enhancing the accuracy of protein model assessment.
  • These methods contribute to more reliable protein structure prediction pipelines.