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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.

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Related Experiment Video

Updated: Jul 10, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

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Published on: May 31, 2013

SHREC 2025: Protein surface shape retrieval including electrostatic potential.

Taher Yacoub1, Camille Depenveiller1, Atsushi Tatsuma2

  • 1Laboratoire GBCM, EA7528, Conservatoire Nationale des Arts et Métiers, Paris, France.

Computers & Graphics
|July 9, 2026
PubMed
Summary

This study evaluated 15 protein surface shape retrieval methods using electrostatic potential. Methods combining shape and electrostatic potential showed the best performance, even with limited data.

Keywords:
BioinformaticsComputer visionElectrostatic potentialMachine learningProtein shape classificationProtein shape retrieval

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Structural Biology

Background:

  • Protein surface shape is crucial for molecular interactions.
  • Efficient retrieval of protein surfaces with specific shapes is a challenge.
  • Electrostatic potential is a key descriptor for molecular surfaces.

Purpose of the Study:

  • To evaluate and compare 15 protein surface shape retrieval methods.
  • To identify methods that perform best on a large dataset of protein surfaces.
  • To assess the impact of electrostatic potential as a molecular surface descriptor.

Main Methods:

  • A dataset of 11,555 protein surfaces was used.
  • Performance evaluation involved metrics like Accuracy, Balanced accuracy, F1 score, Precision, and Recall.
  • Methods were compared based on their ability to retrieve protein surfaces using shape and electrostatic potential.

Main Results:

  • The SHREC 2025 track involved 9 participating teams evaluating 15 methods.
  • Methods integrating electrostatic potential with molecular surface shape achieved the highest retrieval performance.
  • This complementary approach proved effective even for protein classes with limited data.

Conclusions:

  • Combining molecular surface shape with electrostatic potential significantly improves protein surface retrieval.
  • Electrostatic potential is a vital descriptor for enhancing shape-based retrieval.
  • The findings are important for understanding protein interactions and drug discovery.