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Suitability of AF2-derived decoy structures for docking and virtual screening

Determine the suitability of decoy protein structures generated by AlphaFold2-based ensemble diversification methods—specifically reduced multiple sequence alignment AlphaFold2 (rMSA AF2), AF2-cluster, and AlphaFlow—for use as receptor models in downstream docking and virtual screening workflows.

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Background

The paper surveys several AlphaFold2-based approaches that increase structural diversity by generating decoy conformations (rMSA AF2, AF2-cluster, AlphaFlow). Despite producing diverse structures away from the native state, the authors emphasize that it is not yet established whether such decoys are appropriate receptor models for docking or virtual screening, a central step in computer-aided drug design.

This uncertainty directly impacts practical deployment of AF2-generated ensembles for ligand discovery, motivating methods like AF2RAVE to physically rank and select decoys with Boltzmann weights before docking.

References

Several AF2-based techniques, including reduced multiple sequence alignment (rMSA) AF2 (or MSA subsampling AF2), AF2-cluster and AlphaFlow, have been devised to generate distinct decoy structures from native states. However, the suitability of these decoys for subsequent docking and virtual screening remains uncertain.

Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE (2404.07102 - Gu et al., 10 Apr 2024) in Introduction (Section 1)