ArticleScience (New York, N.Y.)2022
Scaffolding protein functional sites using deep learning.
Article in Science (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 218 papers.
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Who cites it
218 citing papers in PubMed.
- Computational design and translational development of TCR-mimic scFv antibodies for peptide-HLA neoantigen targeting.npj drug discovery · 2026Review
- Inverse FoldDir: Structure-conditioned Protein Sequence Design by Dirichlet Flow Matching.bioRxiv : the preprint server for biology · 2026Article
- Sequence and structural determinants of efficacious de novo chimaeric antigen receptors.Nature biomedical engineering · 2026Article
- FAF1 and FAF2 enhance unfolding by p97-UFD1-NPL4 complex enabling rational design of p97 activators.The EMBO journal · 2026Article
- Machine Learning-Driven Nanoscale Synthesis for Electrocatalytic Performance: From Data-Driven Methodologies to Closed-Loop Optimization.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Accelerating protein design by scaling experimental characterization.Nature communications · 2026Article
- Discovery and design of potent cell surface display elements.Nature biotechnology · 2026Article
- Bispecific antibodies for cancer therapy: evolution of structural formats and co-targeting strategies from wet-lab to AI-driven in silico modeling.Cancer letters · 2026Review
- Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.Advanced drug delivery reviews · 2026Review
- Generative AI for controllable protein sequence design: A survey.npj drug discovery · 2026Review
- Ovo, an open-source ecosystem for de novo protein design.Communications biology · 2026Article
- Sequence redesign of glycosyltransferases for enhanced heterologous expression and glycosylation efficiency in Escherichia coli.Nature communications · 2026Article
- Customizing the structure of minimal TIM barrels to craft efficient de novo enzymes.Nature chemical biology · 2026Article
- iPalmT: a new paradigm for palmitoyltransferase discovery via end-to-end deep learning.Oncogene · 2026Article
- Limitations of the refolding pipeline for de novo protein design.Protein science : a publication of the Protein Society · 2026Article
- Supervised Learning for Collagen Segmentation in Bright-Field Histology: A Comparative Evaluation of U-Net and MLP.Annals of biomedical engineering · 2026Article
- Scaffold-Lab: Critical evaluation and ranking of protein backbone generation methods in a unified framework.PLoS computational biology · 2026Article
- Generative Protein Design: From Deep Learning Algorithms to Translational Applications.International journal of molecular sciences · 2026Review
- ProtFormer-Site: Ultra-fast and Accurate Prediction of Protein-Protein Interaction Sites with Protein Language Model.Interdisciplinary sciences, computational life sciences · 2026Article
- Deep learning-enabled scaffolding of spatial arrays of PfCSP epitopes.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
158 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
24 authors.
Funding
Abstract
The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing to prespecify the fold or secondary structure of the scaffold. The first approach, "constrained hallucination," optimizes sequences such that their predicted structures contain the desired functional site. The second approach, "inpainting," starts from the functional site and fills in additional sequence and structure to create a viable protein scaffold in a single forward pass through a specifically trained RoseTTAFold network. We use these two methods to design candidate immunogens, receptor traps, metalloproteins, enzymes, and protein-binding proteins and validate the designs using a combination of in silico and experimental tests.
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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.