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• W2747885724 abstract "Solution stability attributes are one of the key parameters within the production and launching phase of new biopharmaceuticals. Instabilities of active biological compounds can reduce the yield of biopharmaceutical productions, and may induce undesired reactions in patients, such as immunogenic rejections. Protein solution stability thus needs to be engineered and monitored throughout production and storage. In contrast to the gold standard of long-term storage experiments applied in industry, novel experimental and in silico molecular dynamics tools for predicting protein solution stability can be applied within several minutes or hours. Here, a rheological approach in combination with molecular dynamics simulations are presented, for determining and predicting long-term phase behavior of highly concentrated protein solutions. A diversity of liquid phase conditions, including salt type, ionic strength, pH and protein concentration are tested in a Glutathione-S-Transferase (GST) case study, in combination with the enzyme with and without solubility-enhancing Cherry-Tag™. The rheological characterization of GST and Cherry-GST solutions enabled a fast and efficient prediction of protein instabilities without the need of long-term protein phase diagrams. Finally, the strong solubility enhancing properties of the Cherry-Tag™ were revealed by investigating protein surface properties in MD simulations. The tag highly altered the overall surface charge and hydrophobicity of GST, making it less accessible to alteration by the chemical surrounding." @default.
• W2747885724 created "2017-08-31" @default.
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• W2747885724 date "2017-10-01" @default.
• W2747885724 modified "2023-09-27" @default.
• W2747885724 title "Prediction and characterization of the stability enhancing effect of the Cherry-Tag™ in highly concentrated protein solutions by complex rheological measurements and MD simulations" @default.
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• W2747885724 doi "https://doi.org/10.1016/j.ijpharm.2017.08.068" @default.
• W2747885724 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28811118" @default.
• W2747885724 hasPublicationYear "2017" @default.
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