C2Bio

I read the RFD3 paper again more carefully and looked a bit into their source code. There are two versions of this paper: Butcher, J., Krishna, R., Mitra, R.,  et al.  (33 authors). "Atomic functional site scaffolding in biopolymers with RFdiffusion3."  Science , 15 October 2026. doi: 10.1126/science.aeh2982 . Preprint: bioRxiv doi: 10.1101/2025.09.18.676967  (CC-BY 4.0). There are a few major changes in RFD3 compared to earlier versions with very interesting innovative ideas. Two things caught me. The first is a small implementation detail and the most elegant idea in the paper. Every residue gets 4 backbone and 10 side-chain atoms, 10 because tryptophan, the largest canonical sidechain, has that many. Smaller side chains are padded by virtual atoms on Cβ, Cα for glycine. The tensor shape stays constant even with the sequence unknown, and the padding is not inert: "In our formulation, the terminal oxygen of serine and the sulfur of cysteine are different virtual ...

I am glad to see that SAbDab2 came out. This is the major antibody database with structural information. The main changes in SabDab2 in addition to the expansion of data collection is to make the data ready for ML tasks. ★ SAbDab2: the structural antibody database in the age of machine learning  — The Structural Antibody Database (SAbDab) is a publicly available repository of experimentally determined antibody structures, first released in 2013. ★ Artificial intelligence in drug discovery — what it is, where we stand and the path forward — Artificial intelligence (AI) in drug discovery has attracted increasing interest over the past decade. ★ Predicting conformational changes induced by biomolecular interactions — Biomolecular interactions trigger structural changes of protein complexes essential for cellular signaling, regulation, and drug action. ★ De novo design of light-controlled conformational protein switches — Light-responsive proteins offer the ability to cont...

This week we witnessed the release of RFD4-Proteina , a flow-matching foundation model for biomolecular design — Baker Lab × NVIDIA GenAIR. There is no publication out yet. But their gitrepo commit suggests a preprint is coming soon. However, the supported hardware list is very short. You need to have a server grade Nvidia GPU or at least a DGX Spark to run it. Other than RFD4-Proteina, there are also quite a few other protein design related models published. It seems research and publication is this area is accelerating (perhaps with the help of agentic research tools and interests from private sector?). Another trend is the interpretation of reasoning tokens. This is particularly interesting since OpenAI reported that their 6.1 model showed deceptive behavior in the reasoning tokens. In other words, what the model wants you to believe it is doing/thinking, is not what it is actually doing. OpenAI decided not to release their model partly because of this deceptive behavior. Under...

Curated weekly digest of notable AI/ML and biotech developments.  This week's most exciting article may be RFDiffusion 3 paper from Baker's lab. Their preprint on bioRxiv was posted on November 19, 2025--so almost one year before it was accepted by Science.  https://www.science.org/doi/10.1126/science.aeh2982 Original preprint:  https://www.biorxiv.org/content/10.1101/2025.09.18.676967v2.full.pdf Some other paper interesting papers:  ★ A high-resolution protein-RNA binding atlas for structure-aware interaction prediction and post-transcriptional regulatory modeling — RNA-binding proteins (RBPs) control post-transcriptional gene expression by regulating RNA processing, localization, stability, and translation. ★ Mutational constraints on RSV F and its neutralization by antibodies — New antibodies targeting the F protein of respiratory syncytial virus (RSV) have substantially reduced infant hospitalizations 1 . ★ BioMod: Biological Module Tokenization for S...

You draw a figure with Python using matplotlib in PDF, open it in Illustrator to fix one label before the submission deadline, and the text is there but you cannot select it. Click a word and you get a cluster of tiny filled shapes that happen to be letter-shaped. The glyphs are right. The text is gone. This is not an Illustrator problem and it is not a corrupted file. It is a matplotlib default. Tested on matplotlib 3.10.8. Backend defaults do occasionally move, so check yours with matplotlib.__version__ if the behavior below does not match. Type 3 versus Type 42 The PDF specification supports several ways to embed a font. Matplotlib’s PDF backend defaults to Type 3, which defines each glyph as a small PostScript drawing procedure. A Type 3 font is a set of instructions for painting shapes. It carries no reliable mapping back to characters, so a design tool can render it faithfully and still have nothing to hand you when you click. Type 42 wraps a real TrueType font, outlines an...

🧬 Biotech ★ GraPPI: A Self-Supervised Graph Encoder for Transferable Protein–Protein Interaction Modeling — Protein–Protein Interactions (PPIs) are fundamental to cellular processes and represent major targets for therapeutic development. ★ High-throughput metabolic engineering in mammalian cells — The paper introduces a multiplexed shotgun engineering strategy that screens millions of combinatorial genomic solutions to engineer complex phenotypes efficiently in mammalian cells.  ★ What deep learning can and cannot (yet) do for enzyme design — Deep learning has substantially advanced structure-based enzyme design, yet reliably creating highly efficient enzymes remains out of reach. ★ Mapping transcriptional responses to cellular perturbations with RNA fingerprinting — A statistical framework that infers causal regulators from single-cell experiments by mapping their transcriptional responses onto reference perturbation dictionaries.  ★ AI-integrated RNA ...