Nanobodies are of high interest in many fields of medicine and biotechnology due to their high stability, tissue penetration, and engineering adaptability compared to monoclonal antibodies. However,...

Predicting the binding affinity between antigens and antibodies is fundamental to drug discovery and vaccine development. Traditional computational approaches often rely on experimentally...

A prominent application of machine learning in therapeutic antibody design is the development of models that can generate or screen antibody candidates with a high probability of success in manufac...

We present SeedProteo, a diffusion-based model for de novo all-atom protein design. We demonstrate how to repurpose a cutting-edge folding architecture into a powerful generative design framework...

We propose a novel approach for antibody library design that combines deep learning and multi-objective linear programming with diversity constraints. Our method leverages recent advances in sequence...

Current protein binder design largely relies on a decoupled paradigm: generating backbones via unconditioned diffusion followed by sequence filling or refilling with inverse folding models. This...

Designing de novo protein binders to multidomain assemblies remains challenging due to their structural complexity, conformational diversity, and broad functional epitopes. Here, we present an...

A prominent application of machine learning in therapeutic antibody design is the development of models that can generate or screen antibody candidates with a high probability of success in manufac...

Predicting how mutations alter protein–protein binding affinity (ΔΔ G ) is central to protein engineering and therapeutic design, yet current deep learning models often fail to generalize beyond...

Targeted protein degradation (TPD) is a therapeutic strategy to remove disease-causing proteins by routing them to the ubiquitin-proteasome, autophagy, or lysosme machineries. For instance, proteol...

Author summary Proteins underpin much of modern biotechnology. To harness them, we need practical ways to computationally design sequences that meet clear goals while remaining stable and functional....