Protocol for iterative optimization of modified peptides bound to protein targets.

ABSTRACT: Peptides are commonly used as therapeutic agents. However, they suffer from easy degradation and instability. Replacing natural by non-natural amino acids can avoid these problems, and potentially improve the affinity towards the target protein. Here, we present a computational pipeline to optimize peptides based on adding non-natural amino acids while improving their binding affinity. The workflow is an iterative computational evolution algorithm, inspired by the PARCE protocol, that performs single-point mutations on the peptide sequence using modules from the Rosetta framework. The modifications can be guided based on the structural properties or previous knowledge of the biological system. At each mutation step, the affinity to the protein is estimated by sampling the complex conformat

SUBMITTER: Ochoa R 

PROVIDER: S-EPMC9640467 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature