Poster
in
Workshop: 2nd Generative AI for Biology Workshop
AntiDIF: Accurate and Diverse Antibody Specific Inverse Folding with Discrete Diffusion
Nikhil Branson · Charlotte Deane
Keywords: [ Inverse Folding ] [ Antibody ] [ Protein ] [ Diffusion ] [ Structural Biology ] [ Discrete Diffusion ]
Inverse folding is an important step in currentcomputational antibody design. Recently deeplearning methods have made impressive progressin improving the sequence recovery of antibod-ies given their 3D backbone structure. However,inverse folding is often a one-to-many problem,i.e. there are multiple sequences that fold into thesame structure. Previous methods have not takeninto account the diversity between the predictedsequences for a given structure. Here we createAntiDIF an Antibody-specific discrete Diffusionmodel for Inverse Folding. Compared with state-of-the-art methods we show that AntiDIF im-proves diversity between predictions while keep-ing high sequence recovery rates. Furthermore,forward folding of the generated sequences showsgood agreement with the target 3D structure.