C2PO: an ML-powered optimizer of the membrane permeability of cyclic peptides through chemical modification.

ABSTRACT: Peptide drug development is currently receiving due attention as a modality between small and large molecules. Therapeutic peptides represent an opportunity to achieve high potency, selectivity, and reach intracellular targets. A new era in the development of therapeutic peptides emerged with the arrival of cyclic peptides which avoid the limitations of parenteral administration via achieving sufficient oral bioavailability. However, improving the membrane permeability of cyclic peptides remains one of the principal bottlenecks. Here, we introduce a deep learning regression model of cyclic peptide membrane permeability based on publicly available data. The model starts with a chemical structure and goes beyond the limited vocabulary language models to generalize to monomers beyond the ones

SUBMITTER: Aerts R 

PROVIDER: S-EPMC12606850 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature