ArticleProceedings of the National Academy of Sciences of the United States of America2023
The transformative power of transformers in protein structure prediction.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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Who cites it
24 citing papers in PubMed.
- A spectral framework for measuring diversity in multiple sequence alignments.PLoS computational biology · 2026Article
- ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures.Journal of chemical information and modeling · 2026Article
- xBind: an integrated webserver for large language model-enabled cross-molecular protein binding site prediction.Nucleic acids research · 2026Article
- RNAbpFlow: base pair-augmented SE(3) flow matching for conditional RNA 3D structure generation.Nature methods · 2026Article
- ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures.bioRxiv : the preprint server for biology · 2026Article
- AutomataGPT: Transformer-Based Forecasting and Ruleset Inference for Two-Dimensional Cellular Automata.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- NEFFy: a versatile tool for computing the number of effective sequences.Bioinformatics (Oxford, England) · 2026Article
- Review
- The Role of AI-Driven De Novo Protein Design in the Exploration of the Protein Functional Universe.Biology · 2025Review
- Paying attention to attention: High attention sites as indicators of protein family and function in language models.PLoS computational biology · 2025Article
- RNAbpFlow: Base pair-augmented SE(3)-flow matching for conditional RNA 3D structure generation.bioRxiv : the preprint server for biology · 2025Article
- Role of Active Site Residues and Weak Noncovalent Interactions in Substrate Positioning inBiochemistry · 2025Article
- To pack or not to pack: revisiting protein side-chain packing in the post-AlphaFold era.Briefings in bioinformatics · 2025Article
- The physics-AI dialogue in drug design.RSC medicinal chemistry · 2025Review
- Balancing speed and precision in protein folding: a comparison of AlphaFold2, ESMFold, and OmegaFold.Frontiers in genetics · 2025Article
- Advances in Language-Model-Informed Protein-Nucleic Acid Binding Site Prediction.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Using AI-predicted protein structures as a reference to predict loss-of-function activity in tumor suppressor breast cancer genes.Computational and structural biotechnology journal · 2024Article
- Probing Functional Allosteric States and Conformational Ensembles of the Allosteric Protein Kinase States and Mutants: Atomistic Modeling and Comparative Analysis of AlphaFold2, OmegaFold, and AlphaFlow Approaches and Adaptations.The journal of physical chemistry. B · 2024Article
- Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes.Biomedicines · 2024Article
- Tracing unknown tumor origins with a biological-pathway-based transformer model.Cell reports methods · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Transformer neural networks have revolutionized structural biology with the ability to predict protein structures at unprecedented high accuracy. Here, we report the predictive modeling performance of the state-of-the-art protein structure prediction methods built on transformers for 69 protein targets from the recently concluded 15th Critical Assessment of Structure Prediction (CASP15) challenge. Our study shows the power of transformers in protein structure modeling and highlights future areas of improvement.
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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.