ArticleFaraday discussions2022
The impact of AlphaFold2 on experimental structure solution.
Article in Faraday discussions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Artificial intelligence and ultra-high performance computing methods and experiments for drug discovery: virtual screening, deep learning, molecular dynamics simulations, ADMET modelling, and experimental validation.Molecular biomedicine · 2026Review
- Bispecific antibodies for cancer therapy: evolution of structural formats and co-targeting strategies from wet-lab to AI-driven in silico modeling.Cancer letters · 2026Review
- Unlocking the secrets of SARS-CoV-2 nsp3 by combining experiments with AlphaFold2 domain prediction.Life science alliance · 2026Article
- AQuaRef: machine learning accelerated quantum refinement of protein structures.Nature communications · 2025Article
- Advancing time-resolved structural biology: latest strategies in cryo-EM and X-ray crystallography.Nature methods · 2025Review
- Structural and functional characterization of human SLFN14.Nucleic acids research · 2025Article
- Generating Protein Structures for Pathway Discovery Using Deep Learning.Journal of chemical theory and computation · 2024Article
- Generative artificial intelligence performs rudimentary structural biology modeling.Scientific reports · 2024Article
- Generative artificial intelligence performs rudimentary structural biology modeling.bioRxiv : the preprint server for biology · 2024Article
- AlphaFold, allosteric, and orthosteric drug discovery: Ways forward.Drug discovery today · 2023Review
- Using AlphaFold Predictions in Viral Research.Current issues in molecular biology · 2023Review
- AlphaFold2 and its applications in the fields of biology and medicine.Signal transduction and targeted therapy · 2023Review
- Integrating comparative modeling and accelerated simulations reveals conformational and energetic basis of actomyosin force generation.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Exploring AlphaFold2's Performance on Predicting Amino Acid Side-Chain Conformations and Its Utility in Crystal Structure Determination of B318L Protein.International journal of molecular sciences · 2023Article
- The Active Site of the Enzyme 10-Formyl-THFDH in the Honey BeeInternational journal of molecular sciences · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
AlphaFold2 is a machine-learning based program that predicts a protein structure based on the amino acid sequence. In this article, we report on the current usages of this new tool and give examples from our work in the Coronavirus Structural Task Force. With its unprecedented accuracy, it can be utilized for the design of expression constructs,
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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.