ArticleGenome biology2024
FoldPAthreader: predicting protein folding pathway using a novel folding force field model derived from known protein universe.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Application of Enzyme Engineering and Synthetic Biology for Modulated Transformation of Fructooligosaccharides (FOSs) to Elucidate the Catalytic Mechanism of Fructofuranosidases.Foods (Basel, Switzerland) · 2026Article
- Generating Dynamic Structures Through Physics-Based Sampling of Predicted Inter-Residue Geometries.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Unavailability of experimental 3D structural data on protein folding dynamics and necessity for a new generation of structure prediction methods in this context.Bioinformatics (Oxford, England) · 2026Article
- Quality assessment of RNA 3D structure models using deep learning and intermediate 2D maps.Communications biology · 2026Article
- Multimodal pre-training models of molecular representation for drug discovery.National science review · 2026Review
- Accurate Protein Dynamic Conformational Ensembles: Combining AlphaFold, MD, and AmideInternational journal of molecular sciences · 2025Article
- A Computational Perspective to Intermolecular Interactions and the Role of the Solvent on Regulating Protein Properties.Chemical reviews · 2025Review
- Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era.Briefings in bioinformatics · 2025Review
- Physical-aware model accuracy estimation for protein complex using deep learning method.Computational and structural biotechnology journal · 2025Article
- FoldPAthreader: predicting protein folding pathway using a novel folding force field model derived from known protein universe.Genome biology · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Protein folding has become a tractable problem with the significant advances in deep learning-driven protein structure prediction. Here we propose FoldPAthreader, a protein folding pathway prediction method that uses a novel folding force field model by exploring the intrinsic relationship between protein evolution and folding from the known protein universe. Further, the folding force field is used to guide Monte Carlo conformational sampling, driving the protein chain fold into its native state by exploring potential intermediates. On 30 example targets, FoldPAthreader successfully predicts 70% of the proteins whose folding pathway is consistent with biological experimental data.
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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.