GENERATING PROTEIN SEQUENCES USING MACHINE LEARNING TECHNIQUES BASED ON TEMPLATE PROTEIN SEQUENCES

Systems and techniques are described to generate amino acid sequences of target proteins based on amino acid sequences of template proteins using machine learning techniques. The amino acid sequences of the target proteins can be generated based on data that constrains the modifications that can be...

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Bibliographische Detailangaben
Hauptverfasser: TAYLOR, Alex, AMIMEUR, Tileli, SHAVER, Jeremy Martin, KET, Randal Robert
Format: Patent
Sprache:eng ; fre ; ger
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Zusammenfassung:Systems and techniques are described to generate amino acid sequences of target proteins based on amino acid sequences of template proteins using machine learning techniques. The amino acid sequences of the target proteins can be generated based on data that constrains the modifications that can be made to the amino acid sequences of the template proteins. In illustrative examples, the template proteins can include antibodies produced by a non-human mammal that bind to an antigen and the target proteins can correspond to human antibodies with a region having at least a threshold amount of identity with the binding region of the template antibody. Generative adversarial networks can be used to produce the amino acid sequences of the target proteins.