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Ligand Binding Sites02:40

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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.
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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.
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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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CB-Dock3: an enhanced web server for protein-ligand blind docking.

Yang Liu1, Ji Ding1, Jianhong Gan1

  • 1Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, 610065, China.

Nucleic Acids Research
|May 6, 2026
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Summary

CB-Dock3 enhances protein-ligand binding site prediction using an improved docking engine and expanded library. This blind docking tool offers higher accuracy and new features for drug discovery research.

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Area of Science:

  • Computational biology
  • Drug discovery
  • Structural bioinformatics

Background:

  • Protein-ligand interactions are crucial for biological processes and drug development.
  • Blind docking is essential for analyzing novel protein structures from Cryo-EM and AI tools.
  • CB-Dock2, a prior blind docking server, achieved significant user adoption and high performance.

Purpose of the Study:

  • To introduce CB-Dock3, an advanced blind docking platform.
  • To enhance accuracy, usability, and feature set based on user feedback.
  • To provide a robust computational resource for protein-ligand interaction studies.

Main Methods:

  • Development of a refined docking engine and an expanded template library.
  • Implementation of support for diverse file formats.
  • Inclusion of user-defined docking regions and a metal-aware protocol.

Main Results:

  • CB-Dock3 achieved a 67.4% success rate on the CASF-2016 benchmark, a 10.6% absolute improvement over CB-Dock2.
  • Demonstrated superior performance compared to other leading blind docking tools.
  • Successfully integrated features for handling large complexes and retaining metal ions/cofactors.

Conclusions:

  • CB-Dock3 represents a significant advancement in blind docking technology.
  • The platform offers improved accuracy, speed, and accessibility for researchers.
  • CB-Dock3 is a valuable, freely available resource for the scientific community.