Jove
Visualize
Contact Us

Related Experiment Videos

Enzyme classification by ligand binding.

Sergei Izrailev1, Michael A Farnum

  • 1Johnson & Johnson Pharmaceutical Research and Development, Cranbury, New Jersey 08512, USA. sizraile@prdus.jnj.com

Proteins
|October 12, 2004
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

A new risk and issue management system to improve productivity, quality, and compliance in clinical trials.

JAMIA open·2020
Same author

A dimensional warehouse for integrating operational data from clinical trials.

Database : the journal of biological databases and curation·2019
Same author

A late-binding, distributed, NoSQL warehouse for integrating patient data from clinical trials.

Database : the journal of biological databases and curation·2019
Same author

A cross-source, system-agnostic solution for clinical data review.

Database : the journal of biological databases and curation·2019
Same author

Risk-based Monitoring of Clinical Trials: An Integrative Approach.

Clinical therapeutics·2018
Same author

Efficient substructure searching of large chemical libraries: the ABCD chemical cartridge.

Journal of chemical information and modeling·2011
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
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

This study introduces a novel method for enzyme functional classification using ligand-binding data. It leverages existing databases to predict biochemical functions for unknown proteins, aiding in biological discovery.

Area of Science:

  • Biochemistry
  • Bioinformatics
  • Computational Biology

Background:

  • Assigning biochemical function to novel proteins traditionally relies on expert analysis, sequence, and structural modeling.
  • Large-scale protein-ligand interaction databases offer new avenues for functional annotation of enzymes.
  • The Enzyme Commission (EC) classification scheme provides a framework for enzyme categorization.

Purpose of the Study:

  • To introduce a computational method for enzyme functional classification utilizing ligand-binding data.
  • To leverage the BRENDA database and EC classification for predicting enzyme functions.
  • To complement existing sequence and structure-based annotations with ligand interaction information.

Main Methods:

  • Utilizing ligand-binding data from databases like BRENDA for enzyme functional classification.

Related Experiment Videos

  • Employing a query-based approach where a set of ligands for an unknown enzyme searches for similar ligand sets in known enzyme classes.
  • Computing similarity between ligand sets using point set measures based on individual compound similarity.

    • Main Results:

    • The developed method provides functional hypotheses for enzymes with unknown biochemical functions.
    • Cross-validation demonstrates the statistical significance and accuracy of the classification.
    • Successful application of the method is illustrated with several case examples.

    Conclusions:

    • Ligand-binding data offers a powerful approach for enzyme functional annotation.
    • The method effectively predicts enzyme function by matching ligand interaction profiles.
    • This approach enhances the ability to understand and classify newly discovered enzymes.