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+[Drug Discovery Generative AI End-to-End De Novo Proteins; Tensor Networks](https://www.chemicalqdevice.com/drug-discovery-genai-de-novo-proteins) Event Seminar and PDF 04/18/24.
+
+Further modifications were made to a Ni, B., et al. Science Advances 2024 Property-to-sequence generation of de novo proteins using a language diffusion model notebook. 
+Property: Pulling forces learned from protein unfolding experiments using a prior language model.
+Sequence: Generative AI diffusion model de novo arrangement of amino acids in the protein produced.
+Authors’ previous property-to-sequence: Secondary structures specific to a protein are generated, Notebooks available. 
+End-to-end generative models aimed at creating proteins with a specific property are rare. 
+Authors include unfolding energy, mechanical strength with detailed unfolding force-separation curves. 
+Original pull force data for AI training comes from single-molecule technology such as atomic force microscopy, AFM. 
+
+A movie of the author's generated proteins being stretched is available through a literature [Download](https://www.science.org/doi/suppl/10.1126/sciadv.adl4000/suppl_file/sciadv.adl4000_movies_s1_to_s8.zip).
+
+“Here, we report a generative model that predicts protein designs to meet complex nonlinear mechanical property-design objectives. Our model leverages deep knowledge on protein sequences from a pretrained protein language model and maps mechanical unfolding responses to create proteins.”
+- Ni, B., et al., Science Advances, February 07, 2024.