Research graph
References from Prospecting the protein design landscape. Local targets link to admitted publications; unresolved targets remain external evidence.
The past, present and future of de novo protein design
10.1038/s41586-026-10328-7 · 2026 · External reference
10.1101/2022.12.21.521521
10.1101/2022.12.21.521521 · External reference
Robust deep learning–based protein sequence design using ProteinMPNN
10.1126/science.add2187 · 2022 · External reference
De novo design of protein structure and function with RFdiffusion
10.1038/s41586-023-06415-8 · 2023 · External reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · 2021 · External reference
Atomically accurate de novo design of antibodies with RFdiffusion
10.1038/s41586-025-09721-5 · 2026 · External reference
Atomic context‐conditioned protein sequence design using LigandMPNN
10.1038/s41592-025-02626-1 · 2025 · External reference
10.1101/2021.10.04.463034
10.1101/2021.10.04.463034 · External reference
Accurate prediction of protein structures and interactions using a three‐track neural network
10.1126/science.abj8754 · 2021 · External reference
Generalized biomolecular modeling and design with RoseTTAFold all‐atom
10.1126/science.adl2528 · 2024 · External reference
10.1101/2025.08.14.670328
10.1101/2025.08.14.670328 · External reference
Evolutionary‐scale prediction of atomic‐level protein structure with a language model
10.1126/science.ade2574 · 2023 · External reference
10.1101/2025.01.08.631967
10.1101/2025.01.08.631967 · External reference
One‐shot design of functional protein binders with BindCraft
10.1038/s41586-025-09429-6 · 2025 · External reference
10.1101/2025.04.06.647261
10.1101/2025.04.06.647261 · External reference
10.1101/2025.09.30.679633
10.1101/2025.09.30.679633 · External reference
lDDT: a local superposition‐free score for comparing protein structures and models using distance difference tests
10.1093/bioinformatics/btt473 · 2013 · External reference
10.1101/2025.02.10.637595
10.1101/2025.02.10.637595 · External reference
10.64898/2026.04.14.718529
10.64898/2026.04.14.718529 · External reference
10.64898/2026.06.03.729735
10.64898/2026.06.03.729735 · External reference
10.1101/2025.09.18.676967
10.1101/2025.09.18.676967 · External reference
10.1101/2025.11.20.689494
10.1101/2025.11.20.689494 · External reference
Unresolved reference
External reference
10.1101/2025.07.05.663018
10.1101/2025.07.05.663018 · External reference
10.1038/s41587‐026‐03187‐0
10.1038/s41587‐026‐03187‐0 · External reference
Unresolved reference
External reference
Benchmarking all‐atom biomolecular structure prediction with FoldBench
10.1038/s41467-025-67127-3 · 2025 · External reference
Rethinking what pLDDT really tells us about protein flexibility
10.1016/j.str.2025.11.008 · 2025 · External reference
Unresolved reference
External reference
Atom‐level enzyme active site scaffolding using RFdiffusion2
10.1038/s41592-025-02975-x · 2026 · External reference
Computational design of metallohydrolases
10.1038/s41586-025-09746-w · 2026 · External reference
Computational enzyme design by catalytic motif scaffolding
10.1038/s41586-025-09747-9 · 2026 · External reference
10.64898/2026.04.23.720277
10.64898/2026.04.23.720277 · External reference
De novo enzyme design: controlling structure to design function
10.1016/j.sbi.2026.103252 · 2026 · External reference
Structure‐based design of prefusion‐stabilized SARS‐CoV‐2 spikes
10.1126/science.abd0826 · 2020 · External reference
Self‐assembling protein nanoparticles in the design of vaccines
10.1016/j.csbj.2015.11.001 · 2016 · External reference
Deep learning–guided design of dynamic proteins
10.1126/science.adr7094 · 2025 · External reference
10.1016/b978‐0‐12‐381270‐4.00019‐6
10.1016/b978‐0‐12‐381270‐4.00019‐6 · External reference
A generic program for multistate protein design
10.1371/journal.pone.0020937 · 2011 · External reference
Sampling alternative conformational states of transporters and receptors with AlphaFold2
10.7554/elife.75751 · 2022 · External reference
Predicting multiple conformations via sequence clustering and AlphaFold2
10.1038/s41586-023-06832-9 · 2024 · External reference
Unresolved reference
External reference
Scalable emulation of protein equilibrium ensembles with generative deep learning
10.1126/science.adv9817 · 2025 · External reference
Assessing AF2's ability to predict structural ensembles of proteins
10.1016/j.str.2024.09.001 · 2024 · External reference
WaterKit: thermodynamic profiling of protein hydration sites
10.1021/acs.jctc.2c01087 · 2023 · External reference
Superwater as a generative AI framework to predict water molecule positions on protein structures
10.1038/s42004-025-01789-4 · 2025 · External reference
10.1101/2025.03.19.642801
10.1101/2025.03.19.642801 · External reference
Molecular glues for protein–protein interactions: progressing toward a new dream
10.1016/j.chembiol.2024.04.002 · 2024 · External reference
10.1016/b978‐0‐12‐381270‐4.00019‐6
10.1016/b978‐0‐12‐381270‐4.00019‐6 · ExternalCitation · doi-reference
Molecular glues for protein–protein interactions: progressing toward a new dream
10.1016/j.chembiol.2024.04.002 · ExternalCitation · doi-reference
Self‐assembling protein nanoparticles in the design of vaccines
10.1016/j.csbj.2015.11.001 · ExternalCitation · doi-reference
De novo enzyme design: controlling structure to design function
10.1016/j.sbi.2026.103252 · ExternalCitation · doi-reference
Assessing AF2's ability to predict structural ensembles of proteins
10.1016/j.str.2024.09.001 · ExternalCitation · doi-reference
Rethinking what pLDDT really tells us about protein flexibility
10.1016/j.str.2025.11.008 · ExternalCitation · doi-reference
WaterKit: thermodynamic profiling of protein hydration sites
10.1021/acs.jctc.2c01087 · ExternalCitation · doi-reference
Benchmarking all‐atom biomolecular structure prediction with FoldBench
10.1038/s41467-025-67127-3 · ExternalCitation · doi-reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · ExternalCitation · doi-reference
De novo design of protein structure and function with RFdiffusion
10.1038/s41586-023-06415-8 · ExternalCitation · doi-reference
Predicting multiple conformations via sequence clustering and AlphaFold2
10.1038/s41586-023-06832-9 · ExternalCitation · doi-reference
One‐shot design of functional protein binders with BindCraft
10.1038/s41586-025-09429-6 · ExternalCitation · doi-reference
Atomically accurate de novo design of antibodies with RFdiffusion
10.1038/s41586-025-09721-5 · ExternalCitation · doi-reference
Computational design of metallohydrolases
10.1038/s41586-025-09746-w · ExternalCitation · doi-reference
Computational enzyme design by catalytic motif scaffolding
10.1038/s41586-025-09747-9 · ExternalCitation · doi-reference
The past, present and future of de novo protein design
10.1038/s41586-026-10328-7 · ExternalCitation · doi-reference
10.1038/s41587‐026‐03187‐0
10.1038/s41587‐026‐03187‐0 · ExternalCitation · doi-reference
Atomic context‐conditioned protein sequence design using LigandMPNN
10.1038/s41592-025-02626-1 · ExternalCitation · doi-reference
Atom‐level enzyme active site scaffolding using RFdiffusion2
10.1038/s41592-025-02975-x · ExternalCitation · doi-reference
Superwater as a generative AI framework to predict water molecule positions on protein structures
10.1038/s42004-025-01789-4 · ExternalCitation · doi-reference
lDDT: a local superposition‐free score for comparing protein structures and models using distance difference tests
10.1093/bioinformatics/btt473 · ExternalCitation · doi-reference
10.1101/2021.10.04.463034
10.1101/2021.10.04.463034 · ExternalCitation · doi-reference
10.1101/2022.12.21.521521
10.1101/2022.12.21.521521 · ExternalCitation · doi-reference
10.1101/2025.01.08.631967
10.1101/2025.01.08.631967 · ExternalCitation · doi-reference
10.1101/2025.02.10.637595
10.1101/2025.02.10.637595 · ExternalCitation · doi-reference
10.1101/2025.03.19.642801
10.1101/2025.03.19.642801 · ExternalCitation · doi-reference
10.1101/2025.04.06.647261
10.1101/2025.04.06.647261 · ExternalCitation · doi-reference
10.1101/2025.07.05.663018
10.1101/2025.07.05.663018 · ExternalCitation · doi-reference
10.1101/2025.08.14.670328
10.1101/2025.08.14.670328 · ExternalCitation · doi-reference
10.1101/2025.09.18.676967
10.1101/2025.09.18.676967 · ExternalCitation · doi-reference
10.1101/2025.09.30.679633
10.1101/2025.09.30.679633 · ExternalCitation · doi-reference
10.1101/2025.11.20.689494
10.1101/2025.11.20.689494 · ExternalCitation · doi-reference
Structure‐based design of prefusion‐stabilized SARS‐CoV‐2 spikes
10.1126/science.abd0826 · ExternalCitation · doi-reference
Accurate prediction of protein structures and interactions using a three‐track neural network
10.1126/science.abj8754 · ExternalCitation · doi-reference
Robust deep learning–based protein sequence design using ProteinMPNN
10.1126/science.add2187 · ExternalCitation · doi-reference
Evolutionary‐scale prediction of atomic‐level protein structure with a language model
10.1126/science.ade2574 · ExternalCitation · doi-reference
Generalized biomolecular modeling and design with RoseTTAFold all‐atom
10.1126/science.adl2528 · ExternalCitation · doi-reference
Deep learning–guided design of dynamic proteins
10.1126/science.adr7094 · ExternalCitation · doi-reference
Scalable emulation of protein equilibrium ensembles with generative deep learning
10.1126/science.adv9817 · ExternalCitation · doi-reference
A generic program for multistate protein design
10.1371/journal.pone.0020937 · ExternalCitation · doi-reference
10.64898/2026.04.14.718529
10.64898/2026.04.14.718529 · ExternalCitation · doi-reference
10.64898/2026.04.23.720277
10.64898/2026.04.23.720277 · ExternalCitation · doi-reference
10.64898/2026.06.03.729735
10.64898/2026.06.03.729735 · ExternalCitation · doi-reference
Sampling alternative conformational states of transporters and receptors with AlphaFold2
10.7554/elife.75751 · ExternalCitation · doi-reference
