Abstract: Designing new proteins with specific binding capabilities is a challenging task that has the potential to revolutionize many fields, including medicine and material science. Here we introduce ProtFill, a unified method for simultaneous protein structure and sequence design. Distinct from most existing computational design frameworks which focus on either structure or sequence design, our method embraces both representations concurrently. Employing an $SE(3)$ equivariant diffusion graph neural network, our method excels in both sequence prediction and structure recovery. We demonstrate the model's applicability in interface redesign for antibodies as well as other proteins, underscoring the efficacy of our approach and the potential of the diffusion framework in protein design. The code is available at https://anonymous.4open.science/r/ProtFill-1234/.