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Related Concept Videos

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Updated: Apr 6, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Updates to the Integrated Protein-Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark

Thom Vreven1, Iain H Moal2, Anna Vangone3

  • 1Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA.

Journal of Molecular Biology
|August 2, 2015
PubMed
Summary

Updated protein-protein docking and binding affinity benchmarks now include 230 and 179 complexes, respectively. New data improves prediction accuracy for protein interactions and binding energies.

Keywords:
antibody–antigenbinding free energyconformational changeprotein–protein complex structureprotein–protein interface

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Biochemistry

Background:

  • Protein-protein interactions are crucial for cellular functions.
  • Accurate prediction of protein complex structures and binding affinities is essential for drug discovery and understanding biological processes.
  • Existing benchmarks for protein docking and binding affinity prediction require regular updates with high-quality, non-redundant data.

Purpose of the Study:

  • To present an updated and integrated version of widely used protein-protein docking and binding affinity benchmarks.
  • To incorporate new high-quality protein complex structures and experimentally measured binding affinities.
  • To evaluate the performance of existing prediction algorithms on these updated benchmarks.

Main Methods:

  • Integration and curation of non-redundant, high-quality protein-protein complex structures.
  • Inclusion of experimentally determined binding affinities for a subset of complexes.
  • Expansion of the benchmarks with 55 new complexes, including a significant increase in antibody-antigen complexes.
  • Testing of established protein docking and binding affinity prediction algorithms on the updated datasets.

Main Results:

  • The updated docking benchmark contains 230 entries, and the affinity benchmark contains 179 entries.
  • 35 new complexes with experimentally measured binding affinities were added.
  • Antibody-antigen complexes increased by 67% in the docking benchmark and 74% in the affinity benchmark.
  • Prediction accuracy for protein docking reached 38% across all new cases and 50% for rigid-body cases (top 10 predictions).
  • Correlation between predicted and experimental binding energies was observed (r=0.52 overall, r=0.72 for rigid complexes).

Conclusions:

  • The updated benchmarks provide a robust resource for evaluating protein-protein docking and binding affinity prediction methods.
  • The increased number of antibody-antigen complexes specifically enhances the evaluation of these important interactions.
  • Current prediction algorithms show moderate success, highlighting the need for further development in computational approaches for protein interaction studies.