ArticleACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine2023
AlphaFold2 Model Refinement Using Structure Decoys.
Article in ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- ModeHunter: A Package for the Reductionist Analysis, Animation, and Application of Elastic Biomolecular Motion.The journal of physical chemistry. B · 2025Article
- Flexible fitting of AlphaFold2-predicted models to cryo-EM density maps using elastic network models: a methodical affirmation.Bioinformatics advances · 2025Article
- Decoys Reveal Multiple Basins of Attraction for Cryo-Electron-Microscopy Flexible Fitting.Computational structural bioinformatics : international workshop, CSBW 2024, Boston, MA, USA, November 16, 2024, proceedings. Computational Structural Bioinformatics Workshop (2024 : Boston, Mass.) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
AlphaFold2-predicted protein structures inform many modeling techniques in structural biology, including the interpretation of cryogenic electron microscopy (cryo-EM) maps. However, the accuracy of the AlphaFold2 prediction, the quality of the experimental cryo-EM data, and the reliability of the model's alignment with density may affect the accuracy of the interpretation. In this work, we explored a new refinement approach by generating unbiased structural decoys from the AlphaFold2 model via 3DRobot or elastic network model (ENM)-based ModeHunter. Our hope was that some of the decoys would resemble the true structure, and consequently, that the refinement problem could then be reduced to selecting the correct decoy from the decoy set that most closely resembles the experimental cryo-EM map. We explored a map/model pair from the structure of a lipid-preserved respiratory supercomplex, where AlphaFold2 previously struggled (TM-score: 0.52). In this specific case, we observed that the inherent bias of 3DRobot toward compact decoys limited the AlphaFold2 model enhancement (best decoy TM-score: 0.53), whereas ENM is capable of producing extended decoys that significantly improve the accuracy of the AlphaFold2 model (best decoy TM-score: 0.68).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.