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Updated: Feb 6, 2026

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VsNsbench: evaluating AlphaFold3-embed induced-fit mechanism for enhanced virtual screening.

Shu-Kai Gu1,2,3, Chao Shen4, Yu-Wei Yang1

  • 1Faculty of Applied Science, Macao Polytechnic University, Macao, China.

Acta Pharmacologica Sinica
|February 4, 2026
PubMed
Summary

AlphaFold3 (AF3) shows improved ligand-induced modeling for virtual screening (VS) by predicting holo structures. Its performance depends on ligand affinity, highlighting potential for drug discovery but needing multi-state modeling improvements.

Keywords:
AlphaFold3VsNsBenchinduced-fit mechanismvirtual screening

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Area of Science:

  • Computational biology
  • Structural biology
  • Drug discovery

Background:

  • AlphaFold3 (AF3) predicts holo structures, extending AlphaFold2 (AF2).
  • The induced-fit modeling capabilities of AF3 are not fully understood.
  • Benchmarking AF3's performance in virtual screening (VS) is crucial.

Purpose of the Study:

  • To evaluate the virtual screening performance of ligand-induced AlphaFold3 (AF3) holo structures.
  • To compare AF3 holo structures against AF3 apo, experimental apo, and AlphaFold2 (AF2) structures.
  • To investigate the influence of ligand affinity on AF3's induced modeling.

Main Methods:

  • Benchmarking AF3 holo structures on DUD-E and VsNsBench datasets.
  • Comparing enrichment capabilities of AF3 holo vs. apo structures and AF2.
  • Analyzing AF3 performance based on ligand affinity and performing a kinase case study.

Main Results:

  • AF3 holo structures significantly improved enrichment over AF3 apo, experimental apo, and AF2.
  • AF3 performance was superior to experimental holo structures on VsNsBench but inferior on DUD-E.
  • High-affinity ligands enhanced AF3's induced modeling, while low-affinity ligands resulted in poor performance.
  • Direct VS with AF3 showed promise but faced computational efficiency challenges.
  • AF3 successfully modeled inhibitor-specific conformations in a kinase case study (75% success rate).

Conclusions:

  • AF3 effectively incorporates induced-fit modeling for predicting holo structures.
  • AF3's performance is critically dependent on ligand binding affinity.
  • Further improvements are needed for modeling multi-state conformational ensembles, despite promising results.