Design of linear and cyclic peptide binders of different lengths from protein sequence information

Abstract

Structure prediction technology has revolutionised the field of protein design, but key questions such as how to design new functions remain. Many proteins exert their functions through interactions with other proteins, and a significant challenge is designing these interactions effectively. While most efforts have focused on larger, more stable proteins, shorter peptides offer advantages such as lower manufacturing costs, reduced steric hindrance, and the ability to traverse cell membranes when cyclized. However, less structural data is available for peptides and their flexibility makes them harder to design. Here, we present a method to design both novel linear and cyclic peptide binders of varying lengths based solely on a protein target sequence. Our approach does not specify a binding site or the length of the binder, making the procedure completely blind. We demonstrate that linear and cyclic peptide binders of different lengths can be designed with nM affinity in a single shot, and adversarial designs can be avoided through orthogonal in silico evaluation, tripling the success rate. Our protocol, EvoBind2 is freely available https://github.com/patrickbryant1/EvoBind.