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

ASH structure alignment package: sensitivity and selectivity in domain classification.

Daron M Standley1, Hiroyuki Toh, Haruki Nakamura

  • 1Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, Japan. standley@protein.osaka-u.ac.jp

BMC Bioinformatics
|April 5, 2007
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

CD4/CD8 ratio is associated with structural reorganization of vaccine-induced immune responses in people living with HIV.

Frontiers in immunology·2026
Same author

Improved Method for Predicting GPCR-GPCR Interaction Pairs.

Proteins·2026
Same author

An in vivo fitness gene of Toxoplasma, MIC11, is essential for PLP1-mediated egress from host cells.

Nature communications·2026
Same author

Human DHX29 detects nonoptimal codon usage to regulate mRNA stability.

Science (New York, N.Y.)·2026
Same author

Towards the International Conference on Biophysics and Biomedical Sciences: ICBBS 2026.

Biophysics and physicobiology·2026
Same author

Announcement of BPPB paper awards 2025.

Biophysics and physicobiology·2026
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

A new scoring function, ASH, accurately identifies distant evolutionary relationships between proteins using structural alignment. This method enhances protein classification and reveals previously undetectable sequence homologies.

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein evolution

Background:

  • Sequence-based analysis struggles to identify distant evolutionary relationships between proteins.
  • Quantifying structural similarities and differences for evolutionary analysis remains a challenge.

Purpose of the Study:

  • Develop a reliable scoring function to identify proteins with the same CATH topology and SCOP fold classification.
  • Implement the scoring function in the ASH structure alignment package.

Main Methods:

  • Constructed a training set of sequence-unique CATH and SCOP domains.
  • Developed a novel scoring function for structure alignment.
  • Implemented the score in the ASH package, providing source code and a web service.

Related Experiment Videos

Main Results:

  • The ASH score demonstrated high selectivity and sensitivity (0.96 ROC AUC) on a large test set.
  • Identified weak sequence homologies missed by BLAST.
  • Discovered protein pairs with high structural similarity but differing CATH/SCOP classifications.

Conclusions:

  • ASH provides high selectivity and sensitivity for protein domain classification, aiding in defining distantly related protein families.
  • ASH offers competitive CPU performance, making it suitable for large-scale structure classification studies.