@article {70431, title = {De novo design of RNA pseudoknots with deep learning}, journal = {bioRxiv}, year = {2026}, month = {2026 May 22}, abstract = {

RNA design has been hindered by the limited accuracy of 3D structure prediction. Here, we show that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures. In an Eterna competition involving 57 pseudoknots, generative AI methods matched experienced human designers in solving most blind challenges, evaluated by single-nucleotide-resolution chemical mapping, compensatory mutagenesis, and cryogenic electron microscopy. Unexpectedly, AI-generated molecules with accurate secondary structures formed well-ordered 3D folds stabilized by noncanonical tertiary interactions not modeled during design. Success was guided by a RNet foundation model trained on prior chemical mapping data, suggesting that some difficult RNA design tasks may be tractable without first solving RNA 3D structure prediction.

}, doi = {10.64898/2026.05.21.726960}, url = {https://www.biorxiv.org/content/early/2026/05/22/2026.05.21.726960}, author = {Townley, Jill and Kladwang, Wipapat and Baker, David and Blair, Hamish M. and Choe, Christian A. and El Nesr, Gina and Favor, Andrew and Fisker, Eli and Haack, Daniel B. and He, Shujun and Hingey, Jason and Huang, Po-Ssu and Huang, Rui and Joshi, Chaitanya K. and Karagianes, Thomas and Kubaney, Andrew and Li{\`o}, Pietro and Mancino, Adamo and Romano, Jonathan and Rudolfs, Boris and Spellmon, Nicholas and Toor, Navtej and Wu, Vivian and Yu, Zhiheng and Eterna Participants and Das, Rhiju} } @article {47562, title = {Design of a hyperstable 60-subunit protein icosahedron.}, journal = {Nature}, year = {2016}, month = {2016 Jun 15}, abstract = {

The icosahedron is the largest of the Platonic solids, and icosahedral protein structures are widely used in biological systems for packaging and transport. There has been considerable interest in repurposing such structures for applications ranging from targeted delivery to multivalent immunogen presentation. The ability to design proteins that self-assemble into precisely specified, highly ordered icosahedral structures would open the door to a new generation of protein containers with properties custom-tailored to specific applications. Here we describe the computational design of a 25-nanometre icosahedral nanocage that self-assembles from trimeric protein building blocks. The designed protein was produced in Escherichia coli, and found by electron microscopy to assemble into a homogenous population of icosahedral particles nearly identical to the design model. The particles are stable in 6.7 molar guanidine hydrochloride at up to 80 degrees Celsius, and undergo extremely abrupt, but reversible, disassembly between 2 molar and 2.25 molar guanidinium thiocyanate. The icosahedron is robust to genetic fusions: one or two copies of green fluorescent protein (GFP) can be fused to each of the 60 subunits to create highly fluorescent {\textquoteright}standard candles{\textquoteright} for use in light microscopy, and a designed protein pentamer can be placed in the centre of each of the 20 pentameric faces to modulate the size of the entrance/exit channels of the cage. Such robust and customizable nanocages should have considerable utility in targeted drug delivery, vaccine design and synthetic biology.

}, issn = {1476-4687}, doi = {10.1038/nature18010}, author = {Hsia, Yang and Bale, Jacob B and Gonen, Shane and Shi, Dan and Sheffler, William and Fong, Kimberly K and Nattermann, Una and Xu, Chunfu and Huang, Po-Ssu and Ravichandran, Rashmi and Yi, Sue and Davis, Trisha N and Gonen, Tamir and King, Neil P and Baker, David} } @article {45637, title = {High thermodynamic stability of parametrically designed helical bundles.}, journal = {Science}, volume = {346}, year = {2014}, month = {2014 Oct 24}, pages = {481-5}, abstract = {

We describe a procedure for designing proteins with backbones produced by varying the parameters in the Crick coiled coil-generating equations. Combinatorial design calculations identify low-energy sequences for alternative helix supercoil arrangements, and the helices in the lowest-energy arrangements are connected by loop building. We design an antiparallel monomeric untwisted three-helix bundle with 80-residue helices, an antiparallel monomeric right-handed four-helix bundle, and a pentameric parallel left-handed five-helix bundle. The designed proteins are extremely stable (extrapolated ΔGfold \> 60 kilocalories per mole), and their crystal structures are close to those of the design models with nearly identical core packing between the helices. The approach enables the custom design of hyperstable proteins with fine-tuned geometries for a wide range of applications.

}, issn = {1095-9203}, doi = {10.1126/science.1257481}, author = {Huang, Po-Ssu and Oberdorfer, Gustav and Xu, Chunfu and Pei, Xue Y and Nannenga, Brent L and Rogers, Joseph M and DiMaio, Frank and Gonen, Tamir and Luisi, Ben and Baker, David} }