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Related Experiment Videos

Structure-based active site profiles for genome analysis and functional family subclassification.

Stephen A Cammer1, Brian T Hoffman, Jeffrey A Speir

  • 1GeneFormatics Inc., 5830 Oberlin Drive, San Diego, CA 92121, USA.

Journal of Molecular Biology
|November 19, 2003
PubMed
Summary

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An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

Protein science : a publication of the Protein Society·2017

Structure-based active site profiling accurately classifies protein families and subtypes. This method identifies conserved residues and their 3D arrangement, improving functional site recognition and drug design.

Area of Science:

  • Biochemistry and structural biology
  • Computational biology and bioinformatics
  • Drug discovery and medicinal chemistry

Background:

  • Protein active sites are crucial for function, but classification based on sequence similarity is often insufficient.
  • Previous methods like fuzzy functional forms (FFFs) identify conserved residues but struggle with detailed subclassification.
  • A need exists for methods that can discern functional differences within protein families based on active site structure.

Purpose of the Study:

  • To develop a novel 3D active-site profiling method for detailed protein family subclassification.
  • To utilize fuzzy functional forms (FFFs) to identify residues in the spatial environment surrounding active sites.
  • To create a scoring function for accurate discrimination between true functional sites and geometrically similar non-functional sites.

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Main Methods:

  • Developed 3D active-site profiling by extending fuzzy functional forms (FFFs) to include residues around the active site.
  • Constructed active-site profiles for 193 protein functional families using known structures.
  • Created and validated a scoring function to differentiate functional sites from non-functional but structurally similar sites.

Main Results:

  • Successfully constructed distinct and characteristic active-site profiles for 193 functional families.
  • Validated the scoring function's ability to correctly identify specific functional families in a large-scale human genome analysis.
  • Demonstrated effectiveness in classifying protein kinase subtypes, correcting misclassifications made by global sequence alignment methods.

Conclusions:

  • 3D active-site profiling provides detailed subfamily information, surpassing limitations of global sequence alignment.
  • This method accurately identifies functional subtypes of structurally uncharacterized proteins, such as protein kinases.
  • The insights gained are valuable for designing specific and selective inhibitors in the pharmaceutical industry.