<ul><li>A novel computational framework has been developed for designing spider silk protein sequences with customizable mechanical properties.</li><li>The framework utilizes a GPT-based generative model, trained on curated subsets of the Spider Silkome dataset, to generate biologically plausible spider silk repeat regions.</li><li>The model is able to tailor the mechanical properties of the generated sequences to specific requirements.</li><li>Validation studies have shown the accuracy of the model in predicting mechanical properties and confirming its potential for engineering spider silk-inspired biomaterials.</li></ul>

Customizing Spider Silk: Generative Models with Mechanical Property Conditioning for Protein Engineering

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