ReviewCurrent issues in molecular biology2023
Using AlphaFold Predictions in Viral Research.
Review in Current issues in molecular biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed, 47 citations in OpenAlex.
- Innovative Applications of Artificial Intelligence in Bacteriophage Research: A New Chapter in Future Medicine.Microorganisms · 2026Review
- Structure prediction and drug screening targeting monkeypox virus polymerase and surface proteins.Journal of computer-aided molecular design · 2026Article
- Immunoinformatics-driven multi-epitope vaccine design as a promising strategy against multidrug-resistant pathogens: a comprehensive review.Folia microbiologica · 2026Review
- AI-Driven Approaches for the Detection, Classification, and Surveillance of Viral Pathogens: Current Advances, Challenges, and Future Directions.Pathogens (Basel, Switzerland) · 2026Review
- Structural basis of porcine reproductive and respiratory syndrome virus 2 neutralization by a GP4-targeting monoclonal antibody.The Journal of general virology · 2026Article
- From structure to design: experimental and AI-driven approaches in receptor-binding protein engineering for reprogramming phage host range.Archives of microbiology · 2026Review
- Acquisition of amantadine resistance via M gene reassortment in canine H3N2 influenza virus and elucidation of the resistance mechanism.Virology journal · 2026Article
- Structural Insights into the Interaction Between a Core-Fucosylated Foodborne Hexasaccharide (HViruses · 2026Article
- Receptor identification and in vivo efficacy of a lytic phage vB_EcoStr-FJ63A against colistin-resistant Escherichia coli.Veterinary research · 2026Article
- Prediction of pre- and postfusion conformations of class I fusion proteins with AlphaFold2.PloS one · 2026Article
- AI-driven drug reposition for pathogens: a new paradigm in pandemic preparedness.Frontiers in chemistry · 2026Review
- The era of "Infectious Diseases+" has arrived: multi-disciplinary integration in pediatric infectious disease prevention and control.Frontiers in pediatrics · 2026Review
- Charting the virosphere: computational synergies of AI and bioinformatics in viral discovery and evolution.Journal of virology · 2025Review
- Addressing infectious diseases in Africa by accelerating drug discovery through data science.Communications medicine · 2025Review
- Biomolecular Interaction Prediction: The Era of AI.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Phage and enzyme therapies in wound infections: From lab to bedside.Chinese medical journal · 2025Review
- Advanced Strategies in Phage Research: Innovations, Applications, and Challenges.Microorganisms · 2025Review
- Integrating chemical artificial intelligence and cognitive computing for predictive analysis of biological pathways: a case for intrinsically disordered proteins.Biophysical reviews · 2025Review
- Unveiling the influence of fastest nobel prize winner discovery: alphafold's algorithmic intelligence in medical sciences.Journal of molecular modeling · 2025Review
- Fast and flu-rious: How to prevent and treat emerging influenza A viruses.PLoS pathogens · 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
4 authors at 2 institutions in 1 country.
Funding
Abstract
Elucidation of the tertiary structure of proteins is an important task for biological and medical studies. AlphaFold, a modern deep-learning algorithm, enables the prediction of protein structure to a high level of accuracy. It has been applied in numerous studies in various areas of biology and medicine. Viruses are biological entities infecting eukaryotic and procaryotic organisms. They can pose a danger for humans and economically significant animals and plants, but they can also be useful for biological control, suppressing populations of pests and pathogens. AlphaFold can be used for studies of molecular mechanisms of viral infection to facilitate several activities, including drug design. Computational prediction and analysis of the structure of bacteriophage receptor-binding proteins can contribute to more efficient phage therapy. In addition, AlphaFold predictions can be used for the discovery of enzymes of bacteriophage origin that are able to degrade the cell wall of bacterial pathogens. The use of AlphaFold can assist fundamental viral research, including evolutionary studies. The ongoing development and improvement of AlphaFold can ensure that its contribution to the study of viral proteins will be significant in the future.
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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.