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Related Concept Videos

¹H NMR Chemical Shift Equivalence: Homotopic and Heterotopic Protons01:03

¹H NMR Chemical Shift Equivalence: Homotopic and Heterotopic Protons

Protons in identical electronic environments within a molecule are chemically equivalent and have the same chemical shift. The replacement test is a useful tool to identify chemical equivalence and predict NMR spectra. A substituent replaces each of the protons being examined and the resulting molecules are compared. If the same molecule is obtained, the protons are equivalent or homotopic. Replacement of any hydrogens in ethane by chlorine yields chloroethane because all six protons are...
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Related Experiment Video

Updated: Jun 6, 2026

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
08:29

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Published on: April 19, 2019

The LabelHash algorithm for substructure matching.

Mark Moll1, Drew H Bryant, Lydia E Kavraki

  • 1Department of Computer Science, Rice University, Houston, TX 77005, USA. mmoll@rice.edu

BMC Bioinformatics
|November 13, 2010
PubMed
Summary
This summary is machine-generated.

LabelHash is a novel algorithm for efficiently matching protein substructural motifs to large structure databases. This computational method accelerates the identification of protein function, aiding disease research and therapeutic design.

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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

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Last Updated: Jun 6, 2026

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
08:29

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Published on: April 19, 2019

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein science

Background:

  • Many proteins have known structures but unknown functions, hindering disease understanding and drug discovery.
  • Experimental methods for protein function determination are costly and time-intensive.
  • Computational approaches leveraging structural and chemical similarity can expedite function prediction.

Purpose of the Study:

  • To introduce LabelHash, a new algorithm for substructural motif matching in protein structure databases.
  • To demonstrate the efficiency and versatility of LabelHash in identifying protein functional relationships.

Main Methods:

  • LabelHash employs a two-phase approach: preprocessing for rapid partial motif matching and expansion to complete matches.
  • The algorithm was evaluated using three case studies, including enolase superfamily identification and benchmarking against the Catalytic Site Atlas.
  • Performance was assessed on the non-redundant Protein Data Bank, with parallel processing achieving results in minutes.

Main Results:

  • LabelHash accurately identifies protein functional homologs using substructural motifs.
  • The algorithm demonstrates high efficiency, matching motifs against the entire Protein Data Bank (PDB) in minutes when run in parallel.
  • Successful identification of functional homologs was achieved even beyond twilight zone sequence identity and fold similarity.

Conclusions:

  • LabelHash is an efficient and versatile tool for large-scale substructure matching in bioinformatics.
  • The algorithm's speed and accuracy facilitate the discovery of protein function and evolutionary relationships.
  • LabelHash aids in identifying functional homologs, even when sequence or fold similarity is low.