Design of linear and cyclic peptide binders from protein sequence information.

Structure prediction technology has transformed protein design, yet key challenges remain, particularly in designing novel functions. Many proteins function through interactions with other proteins, making the rational design of these interactions a central problem. While most efforts focus on large, stable proteins, shorter peptides offer advantages such as lower manufacturing costs, reduced steric hindrance, and improved cell permeability when cyclised. However, their flexibility and limited structural data make them difficult to design. Here, we introduce EvoBind2, a method for designing novel linear and cyclic peptide binders of varying lengths using only the sequence of a target protein. Unlike existing approaches, EvoBind2 does not require prior knowledge of binding sites or predefined binder lengths, making it a fully blind design process. For one target protein, we demonstrate that linear and cyclic peptide binders of different lengths can be designed in a single shot, and adversarial designs can be avoided through orthogonal in silico evaluation.