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

Approximate multiple protein structure alignment using the sum-of-pairs distance.

Jieping Ye1, Ravi Janardan

  • 1Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA. jieping@cs.umn.edu

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|February 11, 2005
PubMed
Summary

This study introduces a novel algorithm for multiple protein structure alignment, generating a consensus protein. The method rapidly converges, offering an approximation to optimal alignment for protein structure analysis.

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

scDifformer: diffusion-based post-training for virtual cell modeling across large-scale single-cell data.

Nucleic acids research·2026
Same author

Author Correction: UKB-MDRMF: a multi-disease risk and multimorbidity framework based on UK biobank data.

Nature communications·2026
Same author

MyESL: A Software for Evolutionary Sparse Learning in Molecular Phylogenetics and Genomics.

Molecular biology and evolution·2025
Same author

3D vector field-guided toolpathing for 3D bioprinting.

Communications engineering·2025
Same author

Rhizosphere microbial diversity and functional roles in tea cultivars: insights from high-throughput sequencing and functional isolates.

Plant signaling & behavior·2025
Same author

LLaFS++: Few-Shot Image Segmentation With Large Language Models.

IEEE transactions on pattern analysis and machine intelligence·2025

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein structure analysis

Background:

  • Multiple protein structure alignment is crucial for understanding protein function and evolution.
  • Existing methods may not efficiently handle large datasets or provide optimal solutions.
  • Developing accurate and efficient algorithms for protein structure alignment remains a challenge.

Purpose of the Study:

  • To present a novel heuristic algorithm for multiple protein structure alignment.
  • To generate a consensus (pseudo) protein from an aligned set of protein structures.
  • To approximate the optimal multiple structure alignment by minimizing pairwise distances.

Main Methods:

  • The algorithm uses a center-star-like approach for correspondence, analogous to multiple sequence alignment.

Related Experiment Videos

  • Protein structures are represented as sets of unit vectors.
  • Iterative refinement of rotation matrices aligns structures and derives a new consensus until convergence.
  • The sum of pairwise distances is compactly represented as distances to the consensus.

    • Main Results:

    • The algorithm successfully computes multiple structure alignments and generates consensus proteins.
    • Experimental results demonstrate rapid convergence on various protein families.
    • The heuristic approach provides a good approximation to optimal multiple structure alignment.

    Conclusions:

    • The presented algorithm offers an efficient and effective method for multiple protein structure alignment.
    • The consensus protein generation aids in identifying conserved structural features.
    • The rapid convergence suggests scalability for large-scale structural bioinformatics studies.