This study is an expansion by AI of eight public articles on AlphaFold and predicted protein structures, each published under the Creative Commons Attribution 4.0 licence and read in full from PubMed Central: the AlphaFold paper of 2021, the AlphaFold 3 paper of 2024, the two database papers of 2022 and 2024, and four independent assessments (against crystallographic density maps, across structural biology applications, for docking drugs to receptors, and for proteins with more than one fold). Every passage in a block quote is one of these texts, word for word, and its source line names the saved file; the rest is AI writing. The study does not use IATHEON's records. Nothing here is medical, clinical or investment advice. The readings through the works named are this study's interpretation.
| Source | Venue | Licence | Saved file | Read from |
|---|---|---|---|---|
| Jumper et al. 2021, Highly accurate protein structure prediction with AlphaFold | Nature | CC BY 4.0 | jumper-2021-highly-accurate-protein-structure | https://pmc.ncbi.nlm.nih.gov/articles/PMC8371605/ |
| Varadi et al. 2022, AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models | Nucleic Acids Research | CC BY 4.0 | varadi-2022-alphafold-protein-structure-database | https://pmc.ncbi.nlm.nih.gov/articles/PMC8728224/ |
| Abramson et al. 2024, Accurate structure prediction of biomolecular interactions with AlphaFold 3 | Nature | CC BY 4.0 | abramson-2024-accurate-structure-prediction-biomolecular | https://pmc.ncbi.nlm.nih.gov/articles/PMC11168924/ |
| Terwilliger et al. 2023, AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination | Nature Methods | CC BY 4.0 | terwilliger-2023-alphafold-predictions-are-valuable | https://pmc.ncbi.nlm.nih.gov/articles/PMC10776388/ |
| Akdel et al. 2022, A structural biology community assessment of AlphaFold2 applications | Nature Structural & Molecular Biology | CC BY 4.0 | akdel-2022-structural-biology-community-assessment | https://pmc.ncbi.nlm.nih.gov/articles/PMC9663297/ |
| Karelina et al. 2023, How accurately can one predict drug binding modes using AlphaFold models? | eLife | CC BY 4.0 | karelina-2023-how-accurately-can-one | https://pmc.ncbi.nlm.nih.gov/articles/PMC10746139/ |
| Wayment-Steele et al. 2023, Predicting multiple conformations via sequence clustering and AlphaFold2 | Nature | CC BY 4.0 | waymentsteele-2023-predicting-multiple-conformations-via | https://pmc.ncbi.nlm.nih.gov/articles/PMC10808063/ |
| Varadi et al. 2024, AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences | Nucleic Acids Research | CC BY 4.0 | varadi-2024-alphafold-protein-structure-database | https://pmc.ncbi.nlm.nih.gov/articles/PMC10767828/ |
The eight texts were retrieved from PubMed Central on 2026-10-06; sources/manifest.json gives the licence evidence for each. This book was written on 2026-10-07.
Bibliography
- John Jumper and others, Highly accurate protein structure prediction with AlphaFold (2021).
- Mihaly Varadi and others, AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models (2022).
- Mihaly Varadi and others, AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences (2024).
- Josh Abramson and others, Accurate structure prediction of biomolecular interactions with AlphaFold 3 (2024).
- Thomas C. Terwilliger and others, AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination (2023).
- Mehmet Akdel and others, A structural biology community assessment of AlphaFold2 applications (2022).
- Masha Karelina and others, How accurately can one predict drug binding modes using AlphaFold models? (2023).
- Hannah K. Wayment-Steele and others, Predicting multiple conformations via sequence clustering and AlphaFold2 (2023).
- Andriy Kryshtafovych and others, Critical assessment of methods of protein structure prediction (CASP)—Round XIV (2021).
- Andriy Kryshtafovych and others, Critical assessment of methods of protein structure prediction (CASP)—Round XV (2023).
- Kiersten M. Ruff and Rohit V. Pappu, AlphaFold and Implications for Intrinsically Disordered Proteins (2021).
- Jiankun Lyu and others, AlphaFold2 structures guide prospective ligand discovery (2024).
- Minkyung Baek and others, Accurate prediction of protein structures and interactions using a three-track neural network (2021).