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Pharmacokinetic modeling reveals parameters that govern tumor targeting and delivery by a pH-Low Insertion Peptide (pHLIP).


ABSTRACT: A pH-Low Insertion Peptide (pHLIP) is a pH-sensitive peptide that undergoes membrane insertion, resulting in transmembrane helix formation, on exposure to acidity at a tumor cell surface. As a result, pHLIPs preferentially accumulate within tumors and can be used for tumor-targeted imaging and drug delivery. Here we explore the determinants of pHLIP insertion, targeting, and delivery through a computational modeling approach. We generate a simple mathematical model to describe the transmembrane insertion process and then integrate it into a pharmacokinetic model, which predicts the tumor vs. normal tissue biodistribution of the most studied pHLIP, "wild-type pHLIP," over time after a single intravenous injection. From these models, we gain insight into the various mechanisms behind pHLIP tumor targeting and delivery, as well as the various biological parameters that influence it. Furthermore, we analyze how changing the properties of pHLIP can influence the efficacy of tumor targeting and delivery, and we predict the properties for optimal pHLIP phenotypes that have superior tumor targeting and delivery capabilities compared with wild-type pHLIP.

SUBMITTER: Svoronos AA 

PROVIDER: S-EPMC7817199 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Pharmacokinetic modeling reveals parameters that govern tumor targeting and delivery by a pH-Low Insertion Peptide (pHLIP).

Svoronos Alexander A AA   Engelman Donald M DM  

Proceedings of the National Academy of Sciences of the United States of America 20201221 1


A pH-Low Insertion Peptide (pHLIP) is a pH-sensitive peptide that undergoes membrane insertion, resulting in transmembrane helix formation, on exposure to acidity at a tumor cell surface. As a result, pHLIPs preferentially accumulate within tumors and can be used for tumor-targeted imaging and drug delivery. Here we explore the determinants of pHLIP insertion, targeting, and delivery through a computational modeling approach. We generate a simple mathematical model to describe the transmembrane  ...[more]

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