Identification of Protein-Excipient Interaction Hotspots Using Computational Approaches.
Identification of Protein-Excipient Interaction Hotspots Using Computational Approaches.
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DOI：
10.3390/ijms17060853
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发表时间：
2016-06-01
影响因子：
5.6
通讯作者：
Zloh M
中科院分区：
文献类型：
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作者：
Barata TS;Zhang C;Dalby PA;Brocchini S;Zloh M
蛋白质制剂开发依赖于抑制蛋白质-蛋白质相互作用以防止聚集的赋形剂的选择。经验策略涉及使用力降解研究筛选许多赋形剂和缓冲液组合。这些方法不容易提供关于负责赋形剂保护作用的分子间相互作用的信息。本研究描述了一种分子对接方法来筛选和排名相互作用，允许识别蛋白质-辅料热点，以帮助选择要进行实验筛选的辅料。先前发表的果蝇Su（dx）的工作用于开发和验证计算方法，然后用于确定Fab A33的制剂热点。检查常用的赋形剂，并与Fab A33中易于发生蛋白质-蛋白质相互作用的区域进行比较，所述蛋白质-蛋白质相互作用可能导致聚集。这种方法可以提供有关蛋白质制剂中赋形剂保护性相互作用的分子水平信息，以帮助更合理地开发未来制剂。
Protein formulation development relies on the selection of excipients that inhibit protein–protein interactions preventing aggregation. Empirical strategies involve screening many excipient and buffer combinations using force degradation studies. Such methods do not readily provide information on intermolecular interactions responsible for the protective effects of excipients. This study describes a molecular docking approach to screen and rank interactions allowing for the identification of protein–excipient hotspots to aid in the selection of excipients to be experimentally screened. Previously published work with Drosophila Su(dx) was used to develop and validate the computational methodology, which was then used to determine the formulation hotspots for Fab A33. Commonly used excipients were examined and compared to the regions in Fab A33 prone to protein–protein interactions that could lead to aggregation. This approach could provide information on a molecular level about the protective interactions of excipients in protein formulations to aid the more rational development of future formulations.