ArticleNature biotechnology2025
Multistate and functional protein design using RoseTTAFold sequence space diffusion.
Article in Nature biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed.
- Thermodynamic and Structural Determinants of Ni(II), Co(II), and Zn(II) Binding to an XHXXHXH Peptide Motif.Journal of peptide science : an official publication of the European Peptide Society · 2026Article
- Enhanced Sampling of Protein Conformations in AlphaFold3 with Repulsive Bias in the Diffusion Generative Model.JACS Au · 2026Article
- Latent generative search unlocks de novo design of untapped biomolecular interactions at scale.bioRxiv : the preprint server for biology · 2026Article
- Accelerating protein design by scaling experimental characterization.Nature communications · 2026Article
- Diffusion-Based Protein Structure Design: Geometric Modelling, Validation Strategies, and Thermodynamic Challenges.International journal of molecular sciences · 2026Review
- Closing the Translational Gap: Closed-Loop AI Discovery Frameworks for Experimental Validation and Clinical Implementation in Cancer Therapeutics.Cancer medicine · 2026Review
- Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.Advanced drug delivery reviews · 2026Review
- Property guidance for protein sequence generative models with ProteinGuide.Nature biotechnology · 2026Article
- AlphaFold reveals but sometimes distorts an organizational principle of protein folding.bioRxiv : the preprint server for biology · 2026Article
- Experimentally Tuned Protein-RNA Rosetta Score Function using Bayesian Optimization.bioRxiv : the preprint server for biology · 2026Article
- Mixture diffusion model for multimodal antibody design.Briefings in bioinformatics · 2026Article
- Benchmarking Generative AI Protein Models Reveals Differences Between Structural and Sequence-based Approaches.Genomics, proteomics & bioinformatics · 2026Article
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- Protein design and RNA design: Perspectives.Quantitative biology (Beijing, China) · 2026Article
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- Mechanistic insights on spatiotemporal control of Ras-signaling.Biological chemistry · 2026Review
- Improving AlphaFold2 Performance in Virtual Screens Targeting GPCRs by Enhancing Binding-Site Conformational Sampling.Journal of chemical information and modeling · 2026Article
- The latest AI breakthroughs in structural biology: protein binder design and conformational state prediction.Communications biology · 2026Article
- Fold-Switching Proteins.Annual review of biophysics · 2026Review
- The Open Molecular Software Foundation (OMSF) and the Growing Role of Open Source Software in Molecular Modeling.Journal of chemical information and modeling · 2026Review
3 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
19 authors.
Funding
Abstract
Protein denoising diffusion probabilistic models are used for the de novo generation of protein backbones but are limited in their ability to guide generation of proteins with sequence-specific attributes and functional properties. To overcome this limitation, we developed ProteinGenerator (PG), a sequence space diffusion model based on RoseTTAFold that simultaneously generates protein sequences and structures. Beginning from a noised sequence representation, PG generates sequence and structure pairs by iterative denoising, guided by desired sequence and structural protein attributes. We designed thermostable proteins with varying amino acid compositions and internal sequence repeats and cage bioactive peptides, such as melittin. By averaging sequence logits between diffusion trajectories with distinct structural constraints, we designed multistate parent-child protein triples in which the same sequence folds to different supersecondary structures when intact in the parent versus split into two child domains. PG design trajectories can be guided by experimental sequence-activity data, providing a general approach for integrated computational and experimental optimization of protein function.
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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.