Evidence map›Paper›PMID 38603560›Full record

ReviewAnnual review of biomedical data science2024

AlphaFold and Protein Folding: Not Dead Yet! The Frontier Is Conformational Ensembles.

Gregory R Bowman

Abstract readReview
In one paragraph

Review in Annual review of biomedical data science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. AI-Physics-Experiment Trinity for Integrated Protein Dynamics Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  6. A Chromatin Biology Assessment of AlphaFold3.bioRxiv : the preprint server for biology · 2026
    Article
  7. Exploring PadR Proteins for Artificial Enzyme Design.Chembiochem : a European journal of chemical biology · 2026
    Article
  8. bioRxiv : the preprint server for biology · 2026
    Article
  9. Review
  10. Article
  11. Review
  12. Full-Length Context Disrupts Folding of IgG-Binding Domains of Protein A.bioRxiv : the preprint server for biology · 2025
    Article
  13. Review
  14. Generative AI for computational chemistry: A roadmap to predicting emergent phenomena.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. The physics-AI dialogue in drug design.RSC medicinal chemistry · 2025
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Gregory R BowmanDepartments of Biochemistry and Biophysics and Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA; email: grbowman@seas.upenn.edu.

Funding

Project 4 (Genetic modifiers for APOE-associated Alzheimer's disease pathogenesis)U19AG069701 · NIA · MAYO CLINIC JACKSONVILLE · PI Yingxue Ren · 2021 to 2026
$42.0M
MSMs, adaptive sampling, and data sharing on the cloudR01GM124007 · NIGMS · WASHINGTON UNIVERSITY · PI BOWMAN, GREGORY · 2017 to 2021
$2.0M
Structural basis for ApoE4-induced Alzheimer's diseaseRF1AG067194 · NIA · WASHINGTON UNIVERSITY · PI BOWMAN, GREGORY · 2021 to 2021
$1.8M
Understanding and controlling protein energy landscapes by combining simulations and experimentsR35GM152085 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Gregory Bowman · 2024 to 2026
$1.2M
NIA NIH HHS RF1 AG067194NIA NIH HHS U19 AG069701NIGMS NIH HHS R01 GM124007NIGMS NIH HHS R35 GM152085
6 · The paper itself

Abstract

Like the black knight in the classic Monty Python movie, grand scientific challenges such as protein folding are hard to finish off. Notably, AlphaFold is revolutionizing structural biology by bringing highly accurate structure prediction to the masses and opening up innumerable new avenues of research. Despite this enormous success, calling structure prediction, much less protein folding and related problems, "solved" is dangerous, as doing so could stymie further progress. Imagine what the world would be like if we had declared flight solved after the first commercial airlines opened and stopped investing in further research and development. Likewise, there are still important limitations to structure prediction that we would benefit from addressing. Moreover, we are limited in our understanding of the enormous diversity of different structures a single protein can adopt (called a conformational ensemble) and the dynamics by which a protein explores this space. What is clear is that conformational ensembles are critical to protein function, and understanding this aspect of protein dynamics will advance our ability to design new proteins and drugs.

Indexed as

Protein ConformationProtein FoldingProteinsModels, MolecularProteinsmachine learningmolecular dynamicsstructure prediction

Identifiers

PMID38603560
PMCPMC11892350

What OpenQuestion holds

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Registered trials

None linked

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.