Özet:

Peptide therapeutics are new modalities offering several challenges to drug discovery. They are generally less stable and permeable in vivo. The characterization of their lipophilicity cannot be carried out using the traditional in silico or wet octanol/water partition coefficients. The prediction of their in vivo distribution and permeability is also challenging. In this paper, it is demonstrated that the biomimetic properties such as lipophilicity, protein and phospholipid binding can be easily assessed by HPLC using chemically bonded protein and immobilized artificial membrane (IAM) stationary phases. The obtained properties for a set of potential therapeutic peptides with 3 to 33 amino acids have been analysed and it was found that similar characteristics of the properties could be observed as for small molecule drugs. The albumin binding showed correlation with their measured lipophilicity on the C-18 stationary phase with acidic peptides showing stronger than expected albumin binding. The (IAM) chromatography revealed peptide membrane affinity, which was stronger for positively charged peptides (containing arginine) and showed correlation to the alpha-1-acid glycoprotein (AGP) binding, which was also stronger for positively charged compounds. The in vivo volume of distribution and drug efficiency of the peptides have been estimated using the models developed for small molecules. One of the candidate linear peptides has been assessed in various cellular and in vivo assays and the results have confirmed the estimated cell partition and brain to plasma ratio. It can be demonstrated, that up to 21 amino acids, the peaks of the peptides obtained on the protein phase were symmetrical and narrow. The interaction of larger peptides with the protein stationary phases resulted in wide peaks showing multiple equilibrium processes with slow kinetics during chromatography. The larger peptides showed narrow and symmetrical peaks on the IAM column enabling the quantification of peptide - cell membrane interactions.

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