ArticleCellular and molecular life sciences : CMLS2022
Ins and outs of AlphaFold2 transmembrane protein structure predictions.
Article in Cellular and molecular life sciences : CMLS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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Who cites it
67 citing papers in PubMed.
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- The perineurium integrates leptin with its sympathetic outflow to protect against obesity.Nature metabolism · 2026Article
- The Shape of Things to Come: α-Helical Membrane Protein Folding on the Ribosome.Chemical reviews · 2026Review
- Extending structural surfaceomics to identify aberrant conformations of tumor surface proteins as potential immunotherapy targets.bioRxiv : the preprint server for biology · 2026Article
- Computational design of synthetic receptors with programmable signalling activity for enhanced cancer T cell therapy.Nature biomedical engineering · 2026Article
- Bacterial Chemoreceptors Transmit Stimulus Signals Through Coupled Entropic Switches.Journal of molecular biology · 2026Article
- Artificial intelligence-based structural modeling of PSTOL1 receptor kinases in rice and sorghum.Frontiers in plant science · 2026Article
- Exploring the Blueprint of Life: The Innovation in Antibody and Protein Design.Combinatorial chemistry & high throughput screening · 2026Article
- From CASP13 to the Nobel Prize: DeepMind's AlphaFold Journey in Revolutionizing Protein Structure Prediction and Beyond.Current protein & peptide science · 2026Review
- The S190R mutation in RSV-A F protein impairs nirsevimab binding and neutralization capacity.Virus evolution · 2026Article
- A tripartite protein complex promotes DNA transport during natural transformation in Firmicutes.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Deep learning-assisted tools to understand the structural biology of the synapse.Biomedical engineering letters · 2025Review
- Phylogenetic and Structural Analyses of Vesicular Glutamate Transporters.Molecular neurobiology · 2025Article
- A key residue of the extracellular gate provides quality control contributing to ABCG substrate specificity.Nature communications · 2025Article
- Message hidden in α-helices-toward a better understanding of plant ABCG transporters' multispecificity.Plant physiology · 2025Article
- Article
- TBM preferred to AlphaFold 3 for functional models of insect odorant receptors.Computational and structural biotechnology journal · 2025Article
- A Survey of Current Status in AI-Based Topology Prediction of Transmembrane Proteins.Methods in molecular biology (Clifton, N.J.) · 2025Article
- An in silico framework to visualize how cancer-associated mutations influence structural plasticity of the chemokine receptor CCR3.Protein science : a publication of the Protein Society · 2025Article
7 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
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Abstract
Transmembrane (TM) proteins are major drug targets, but their structure determination, a prerequisite for rational drug design, remains challenging. Recently, the DeepMind's AlphaFold2 machine learning method greatly expanded the structural coverage of sequences with high accuracy. Since the employed algorithm did not take specific properties of TM proteins into account, the reliability of the generated TM structures should be assessed. Therefore, we quantitatively investigated the quality of structures at genome scales, at the level of ABC protein superfamily folds and for specific membrane proteins (e.g. dimer modeling and stability in molecular dynamics simulations). We tested template-free structure prediction with a challenging TM CASP14 target and several TM protein structures published after AlphaFold2 training. Our results suggest that AlphaFold2 performs well in the case of TM proteins and its neural network is not overfitted. We conclude that cautious applications of AlphaFold2 structural models will advance TM protein-associated studies at an unexpected level.
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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.