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**PPI-Llama2: *De Novo* Generation of Binding Proteins Conditioned on Target Sequence Alone**
![image/png](https://cdn-uploads.huggingface.co/production/uploads/64cd5b3f0494187a9e8b7c69/jlxqjz0FdmOVd_QUJQtDn.png)

The targeting of disease-driving proteins is a critical goal of biomedicine. However, many of these proteins do not possess accessible small molecule binding pockets and are oftentimes conformationally disordered, precluding binder design via structure-dependent methods. Here, we present **PPI-Llama2**, which leverages Meta's Llama2 autoregressive language model architecture to *de novo* generate protein binders conditioned directly on target sequences. Without relying on structural data and training only on protein-protein interaction (PPI) sequences, PPI-Llama2 effectively learns the evolutionary semantics of PPIs, enabling the generation of both novel and biologically-plausible binders.