ReviewActa crystallographica. Section D, Structural biology2022
Implications of AlphaFold2 for crystallographic phasing by molecular replacement.
Review in Acta crystallographica. Section D, Structural biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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.
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.
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Who cites it
67 citing papers in PubMed.
- Viral Nuclease Inhibitors: Small molecule disruptors of the UL12 alkaline nuclease display broad anti-herpes virus activity.PLoS pathogens · 2026Article
- AI-Predicted Model-Guided Rebuilding of the Experimental Structure of Mouse δ-Aminolevulinic Acid Dehydratase.International journal of molecular sciences · 2026Article
- Viral Nuclease Inhibitors: Small molecule disruptors of the UL12 alkaline nuclease display broad anti-herpes virus activity.bioRxiv : the preprint server for biology · 2026Article
- AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network.Nature methods · 2026Article
- Evaluation of AI-Predicted GH11 Xylanase Models Against a Previously Unreported Experimental Structure: Implications for Conformational Accuracy and Ligand Binding.International journal of molecular sciences · 2026Article
- Antibacterial Drug Discovery: Deep Learning Successes and Challenges through the Structural Biology Lens.Computational and structural biotechnology journal · 2026Review
- High-Throughput Prediction of Protein-Protein Interactions Uncovers Hidden Molecular Networks in Biosynthetic Gene Clusters.Computational and structural biotechnology journal · 2026Article
- Completion of partial structures using Patterson maps with the CrysFormer machine-learning model.Acta crystallographica. Section D, Structural biology · 2025Article
- Article
- Emerging frontiers in protein structure prediction following the AlphaFold revolution.Journal of the Royal Society, Interface · 2025Review
- Slice'N'Dice: maximizing the value of predicted models for structural biologists.Acta crystallographica. Section D, Structural biology · 2025Article
- An outlook on structural biology after AlphaFold: tools, limits and perspectives.FEBS open bio · 2025Review
- SFCalculator: connecting deep generative models and crystallography.bioRxiv : the preprint server for biology · 2025Article
- How the technologies behind self-driving cars, social networks, ChatGPT, and DALL-E2 are changing structural biology.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025Review
- AlphaFold-guided molecular replacement for solving challenging crystal structures.Acta crystallographica. Section D, Structural biology · 2025Article
- Structural Biology for Target Identification and Validation.Methods in molecular biology (Clifton, N.J.) · 2025Article
- The 1.3 Å resolution structure of the truncated group Ia type IV pilin from Pseudomonas aeruginosa strain P1.Acta crystallographica. Section D, Structural biology · 2024Article
- The success rate of processed predicted models in molecular replacement: implications for experimental phasing in the AlphaFold era.Acta crystallographica. Section D, Structural biology · 2024Article
- Allostery Illuminated: Harnessing AI and Machine Learning for Drug Discovery.ACS medicinal chemistry letters · 2024Review
- AlphaFold two years on: Validation and impact.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
7 more citing papers are in PubMed but not listed here.
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
The AlphaFold2 results in the 14th edition of Critical Assessment of Structure Prediction (CASP14) showed that accurate (low root-mean-square deviation) in silico models of protein structure domains are on the horizon, whether or not the protein is related to known structures through high-coverage sequence similarity. As highly accurate models become available, generated by harnessing the power of correlated mutations and deep learning, one of the aspects of structural biology to be impacted will be methods of phasing in crystallography. Here, the data from CASP14 are used to explore the prospects for changes in phasing methods, and in particular to explore the prospects for molecular-replacement phasing using in silico models.
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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.