ReviewBotanical studies2025
Analysing protein complexes in plant science: insights and limitation with AlphaFold 3.
Review in Botanical studies, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- An Integrated Computational and Biophysical Approach for Investigating the Structure-Function Impact of blaOXA-58 Mutations in Acinetobacter baumannii.Molecular biotechnology · 2026Article
- Artificial Intelligence-Assisted Design of Plant-Protein Meat Analogues: Integrating Nutrition, Functionality, and Fibrillation-Based Texturization.Comprehensive reviews in food science and food safety · 2026Review
- Sheep erythrocyte potassium locus highlights MYADM family regulation of electroneutral potassium chloride cotransporters (KCC).BMC genomics · 2026Article
- Structural and immunogenic evaluation of silk proteins from Bombyx mori using advanced bioinformatics and deep learning for biomaterials applications.Journal, genetic engineering & biotechnology · 2026Article
- AI-enabled protein design facilitates future plant research and crop breeding.Plant physiology · 2026Review
- Heparan sulfate as an attachment factor for ASFV is restricted by host HB-EGF.Cellular and molecular life sciences : CMLS · 2026Article
- The transformative power of structural predictions with AI in plant science.The Plant journal : for cell and molecular biology · 2026Review
- Review
- AI-driven insights into protein misfolding and innate immunity in neurodegenerative diseases.Frontiers in immunology · 2026Review
- Computational Design and Glycoengineering of Interferon-Lambda for Nasal Prophylaxis Against Respiratory Viruses.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Article
- Functional Ingredients: From Molecule to Market-AI-Enabled Design, Bioavailability, Consumer Impact, and Clinical Evidence.Foods (Basel, Switzerland) · 2025Review
- Regulatory functions of AcuK and AcuM transcription factors in fungal metabolic adaptation, stress response, and virulence.Frontiers in cellular and infection microbiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
AlphaFold 3 (AF3), an artificial intelligence (AI)-based software for protein complex structure prediction, represents a significant advancement in structural biology. Its flexibility and enhanced scalability have unlocked new applications in various fields, specifically in plant science, including improving crop resilience and predicting the structures of plant-specific proteins involved in stress responses, signalling pathways, and immune responses. Comparisons with existing tools, such as ClusPro and AlphaPulldown, highlight AF3's unique strengths in sequence-based interaction predictions and its greater adaptability to various biomolecular structures. However, limitations persist, including challenges in modelling large complexes, protein dynamics, and structures from underrepresented plant proteins with limited evolutionary data. Additionally, AF3 encounters difficulties in predicting mutation effects on protein interactions and DNA binding, which can be improved with molecular dynamics and experimental validation. This review presents an overview of AF3's advancements, using examples in plant and fungal research, and comparisons with existing tools. It also discusses current limitations and offers perspectives on integrating molecular dynamics and experimental validation to enhance its capabilities.
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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.