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

Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selection.

Dylan Chivian1, David Baker

  • 1Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.

Nucleic Acids Research
|September 15, 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

CASP11 refinement experiments with ROSETTA.

Proteins·2015
Same author

Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression.

Protein science : a publication of the Protein Society·2015
Same author

Unique double-ring structure of the peroxisomal Pex1/Pex6 ATPase complex revealed by cryo-electron microscopy.

Proceedings of the National Academy of Sciences of the United States of America·2015
Same author

Mechanistic Analysis of an Engineered Enzyme that Catalyzes the Formose Reaction.

Chembiochem : a European journal of chemical biology·2015
Same author

Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces.

Science (New York, N.Y.)·2015
Same author

Designing Two-Dimensional Protein Arrays through Fusion of Multimers and Interface Mutations.

Nano letters·2015
Same journal

Correction to 'New origin firing is inhibited by APC/CCdh1 activation in S-phase after severe replication stress'.

Nucleic acids research·2026
Same journal

VeloRM: disentangling pre- and post-splicing RNA modification dynamics at single-cell resolution.

Nucleic acids research·2026
Same journal

Accessibility of telomeric overhangs to stabilizing small-molecule ligands.

Nucleic acids research·2026
Same journal

Multivalent interactions mediate SNAIL transcription factor stimulation of the nucleosome deacetylase activity of the CoREST complex.

Nucleic acids research·2026
Same journal

Genome-wide mapping of DNA G-quadruplexes in Trypanosoma brucei chromatin reveals enrichment in coding regions and transcription start sites.

Nucleic acids research·2026
Same journal

Correction to 'The Gene Ontology knowledgebase in 2026'.

Nucleic acids research·2026
See all related articles

This study introduces K*Sync, a novel method for sequence-to-structure alignment in protein homology modeling. K*Sync improves accuracy by integrating multiple protein features into a dynamic programming approach, enhancing protein structure prediction.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Modeling

Background:

  • Homology modeling accuracy is often limited by sequence-to-structure alignment quality.
  • Aligning sequences to distant or topologically equivalent protein structures presents significant challenges.

Purpose of the Study:

  • To develop a systematic and accurate approach for sequence-to-structure alignment.
  • To enhance the reliability of homology models by improving alignment generation and selection.

Main Methods:

  • Introduced K*Sync, a dynamic programming method for sequence-to-structure alignment.
  • Utilized a scoring function combining multiple protein features, including a novel measure of sequence region's "obligateness" to the protein fold.
  • Generated large ensembles of diverse alignments by systematically varying feature weights.

Related Experiment Videos

  • Evaluated alignment ensembles using methods like consensus, hydrophobic burial, and energy functions.

    • Main Results:

    • K*Sync demonstrated effectiveness in generating and selecting accurate alignments.
    • The approach improved the quality of homology models.
    • Investigated the impact of loop modeling and backbone optimization on model quality and selection.

    Conclusions:

    • K*Sync provides a robust foundation for homology modeling.
    • The method enhances the accuracy of protein structure prediction through improved sequence-to-structure alignment.
    • K*Sync is integrated into the Robetta server's homology modeling module.