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 Experiment Videos

Comparing programs for rigid-body multiple structural superposition of proteins.

Anthony D Hill1, Peter J Reilly

  • 1Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011-2230, USA.

Proteins
|March 29, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Single-nucleus RNA-seq dissection of choroid plexus tumor cell heterogeneity.

The EMBO journal·2024
Same author

Carboxylic ester hydrolases: Classification and database derived from their primary, secondary, and tertiary structures.

Protein science : a publication of the Protein Society·2016
Same author

Scoring functions for AutoDock.

Methods in molecular biology (Clifton, N.J.)·2015
Same author

Carbohydrate-binding module tribes.

Biopolymers·2014
Same author

Fatty acid synthesis enzyme clans.

Biotechnology letters·2014
Same author

Molecular mechanism of a hotdog-fold acyl-CoA thioesterase.

Chemistry (Weinheim an der Bergstrasse, Germany)·2014
Same journal

Engineered HSP90-MP65 Bivalent Fusion Antigen: A Novel Vaccine Candidate Against Invasive Candidiasis.

Proteins·2026
Same journal

Physics-Based Energy Functions for Computational Protein Design.

Proteins·2026
Same journal

Impact of Stabilizing Osmolytes on the Conformational Dynamics of Human and Rat Islet Amyloid Polypeptides.

Proteins·2026
Same journal

Stabilization of Bone Morphogenetic Protein-2 at Physiological pH: Contrasting Roles of CHAPS and Arginine in Aggregation Inhibition.

Proteins·2026
Same journal

Structural Insights Into the Function of Leishmania major Adenylosuccinate Lyase.

Proteins·2026
Same journal

Generalizing the Gaussian Network Model: Spanning-Tree Thermodynamics Shows Entropy-Driven KRAS Activation.

Proteins·2026
See all related articles

Human-guided protein structure superposition methods generally outperform automated techniques. A new program, PyMSS, integrates human interaction for improved protein structure alignment, offering better results than some automated algorithms.

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Molecular modeling

Background:

  • Protein structure superposition is crucial for comparative analysis and understanding evolutionary relationships.
  • Existing automated methods for protein structure alignment have limitations in accuracy and efficiency across diverse protein families.

Purpose of the Study:

  • To compare the effectiveness of different protein structure superposition methods.
  • To evaluate the performance of human-guided versus automated residue identification techniques.
  • To introduce a novel program, PyMSS, incorporating interactive superposition algorithms.

Main Methods:

  • Comparison of various protein structure superposition programs using four distinct protein families.
  • Evaluation of algorithms relying on human-identified key residues versus automated residue selection.

Related Experiment Videos

  • Testing a genetic algorithm approach and assessing the performance of the PyMSS program.

    • Main Results:

    • Human-guided superposition algorithms demonstrated superior success rates compared to automated methods.
    • The MASS program showed variable efficiency, successfully aligning some families but failing with others.
    • The genetic algorithm improved superpositions from MODELLER and STAMP, but not from neighbor-joining or pseudostar algorithms.
    • PyMSS, with its interactive algorithms, provided improved superposition results.

    Conclusions:

    • Interactive, human-guided approaches are more reliable for protein structure superposition.
    • Automated methods like MASS, MODELLER, MultiProt, and STAMP exhibit varied performance.
    • The developed PyMSS program offers a valuable tool for enhanced protein structure alignment through user interaction.