GENERATIVE MACHINE LEARNING MODELS FOR PREDICTING FUNCTIONAL PROTEIN SEQUENCES

摘要

The present disclosure provides, in some embodiments, techniques for using generative machine learning models to generate new functional protein sequences based on an input protein structure, such that the new functional protein sequences are structurally similar to the input protein structure but have new and diverse protein sequences. The techniques described herein may be used alone, or in conjunction with structural prediction algorithms and/or to generate diversified gene libraries in directed evolution techniques.