Molecular insights into the improved clinical performance of PEGylated interferon therapeutics: a molecular dynamics perspectiveElectronic supplementary information (ESI) available. See DOI: 10.1039/c7ra12480e
PEGylation is a widely adopted process to covalently attach a polyethylene glycol (PEG) polymer to a protein drug for the purpose of optimizing drug clinical performance. While the outcomes of PEGylation in imparting pharmacological advantages have been examined through experimental studies, the und...
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Main Authors: | , , , , , , , |
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Format: | Journal Article |
Language: | English |
Published: |
09-01-2018
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Online Access: | Get full text |
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Summary: | PEGylation is a widely adopted process to covalently attach a polyethylene glycol (PEG) polymer to a protein drug for the purpose of optimizing drug clinical performance. While the outcomes of PEGylation in imparting pharmacological advantages have been examined through experimental studies, the underlying molecular mechanisms remain poorly understood. Using interferon (IFN) as a representative model system, we carried out comparative molecular dynamics (MD) simulations of free PEG
x
, apo-IFN, and PEG
x
-IFN (
x
= 50, 100, 200, 300) to characterize the molecular-level changes in IFN introduced by PEGylation. The simulations yielded molecular evidence directly linked to the improved protein stability, bioavailability, retention time, as well as the decrease in protein bioactivity with PEG conjugates. Our results indicate that there is a tradeoff between the benefits and costs of PEGylation. The optimal PEG chain length used in PEGylation needs to strike a good balance among the competing factors and maximizes the overall therapeutic efficacy of the protein drug. We anticipate the study will have a broad implication for protein drug design and development, and provide a unique computational approach in the context of optimizing PEGylated protein drug conjugates.
We discovered molecular evidence that links PEGylation to improved clinical performance, yet at the expense of decreased bioactivity. Our computational approach will facilitate PEGylated protein drug design and optimize its overall therapeutic efficacy. |
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Bibliography: | 10.1039/c7ra12480e Electronic supplementary information (ESI) available. See DOI |
ISSN: | 2046-2069 |
DOI: | 10.1039/c7ra12480e |