ArticleNature communications2025
Rapid estimation of protein folding pathways from sequence alone using AlphaFold2.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- The Advantages of AI for Computational Protein Studies and Looking Ahead at the Next Challenges: Single Structures Are Not Enough.Journal of molecular biology · 2026Review
- Stability and cooperativity in chimeric de novo TIM barrels via quarter swapping.Protein science : a publication of the Protein Society · 2026Article
- Beyond Classical Force Fields: Physics-Driven Assessment of the Grappa Machine-Learned Force Field on the FoldBind Dataset.Chemphyschem : a European journal of chemical physics and physical chemistry · 2026Article
- Generating Dynamic Structures Through Physics-Based Sampling of Predicted Inter-Residue Geometries.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
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Authors and funding
2 authors.
Funding
Abstract
AlphaFold2 (AF2) revolutionized protein structure prediction, yet it is often conflated with the protein folding problem. Structure prediction seeks a static conformation, whereas folding concerns the dynamic process of structure formation. We challenge the current status quo, showing that AF2 has implicitly learned some folding principles. Its learned biophysical energy function, though imperfect, enables rapid discovery of folding pathways within minutes. Operating AF2 without multiple sequence alignments (MSAs) or templates forces sampling across its entire energy landscape, akin to ab initio modeling. Among over 7000 proteins, a fraction folds from sequence alone, highlighting the smoothness of AF2's learned surface. Iterating and recycling predictions uncover intermediate structures consistent with experiments, suggesting a "local-first, global-later" mechanism. For designed proteins with optimized local interactions, AF2's landscape becomes too smooth to reveal intermediates. These findings illuminate what AF2 has learned and open avenues for probing protein folding mechanisms and experimental intermediates.
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