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Related Concept Videos

Ligand Binding Sites02:40

Ligand Binding Sites

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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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Conserved Binding Sites01:49

Conserved Binding Sites

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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...
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The Equilibrium Binding Constant and Binding Strength02:18

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The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
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LigandExplorer: An Automated Tool for Ligand Extraction from PDB Structures.

Yaqi Li1,2,3,4, Rongfeng Zou4, Maohua Yang4

  • 1The National and Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha 410081 Hunan, China.

Journal of Chemical Information and Modeling
|February 28, 2026
PubMed
Summary
This summary is machine-generated.

LigandExplorer is an automated pipeline that extracts and categorizes ligands from protein structures, streamlining drug discovery. This tool ensures standardized, up-to-date datasets for computational modeling and molecular design.

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Area of Science:

  • Structural biology
  • Computational chemistry
  • Drug discovery

Background:

  • Protein-ligand complex structural data is vital for drug design.
  • Existing databases often have inconsistent annotations and require extensive processing for large-scale modeling.

Purpose of the Study:

  • To develop an automated pipeline, LigandExplorer, for processing biomolecular complex structures.
  • To identify, extract, and categorize ligands (covalent and noncovalent) for standardized downstream use.

Main Methods:

  • Utilizes residue-level graphs from atomic coordinates, independent of metadata.
  • Integrates LightGBM models for ligand classification (peptides, nucleic acids, phospholipids, carbohydrates, organics, ions) and interaction relevance assessment.
  • Designed as a rerunnable pipeline for continuous updates.

Main Results:

  • Achieved 98.38% structural agreement on the PDBbind v2020 refined set.
  • Successfully processed 97.52% of complexes in the PepBDB dataset.
  • Identified discrepancies primarily due to upstream data inconsistencies.

Conclusions:

  • LigandExplorer automates data cleaning and standardization for biomolecular complex structures.
  • Enables the creation of rapidly refreshed, machine-ready datasets for computational modeling and small-molecule design.
  • Mitigates data-cleaning burdens in drug discovery research.