Advancing Therapeutic Protein Discovery and Development through Comprehensive Computational and Biophysical Characterization
Advancing Therapeutic Protein Discovery and Development through Comprehensive Computational and Biophysical Characterization
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DOI：
10.1021/acs.molpharmaceut.9b00852
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发表时间：
2020-02-01
影响因子：
4.9
通讯作者：
Friess, Wolfgang
中科院分区：
文献类型：
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作者：
Gentiluomo, Lorenzo;Svilenov, Hristo L.;Friess, Wolfgang
治疗性候选蛋白应表现出适合成为药物的有利特性。然而，对于在早期发育阶段有效选择具有所需特征的蛋白质分子，目前还没有完善的指导方针。这样的指导方针只能从大量已发表的研究中产生，这些研究采用正交技术来表征不同配方的治疗性蛋白质。在这项工作中，我们分享了一组不同蛋白质的研究，包括它们的初级序列，纯度数据，以及在不同pH和离子强度下的计算和生物物理特性。我们报告了许多生物物理参数之间的弱线性相关性。我们建议，不同候选治疗蛋白的稳定性比较应该基于多种配方条件下的计算和生物物理特性，因为后者可以在很大程度上决定蛋白质是高于还是低于一定的稳定性阈值。我们使用所呈现的数据集来计算几个稳定性风险评分，这些评分是通过不断增加的分析努力获得的，并显示它们如何与储存期间的蛋白质聚集相关。我们的工作强调了开发可用于早期可发展性评估的综合风险评分的重要性。我们认为，只有基于不同溶液条件下蛋白质稳定性表征的分数才能具有较高的预测精度。
Therapeutic protein candidates should exhibit favorable properties that render them suitable to become drugs. Nevertheless, there are no well-established guidelines for the efficient selection of proteinaceous molecules with desired features during early stage development. Such guidelines can emerge only from a large body of published research that employs orthogonal techniques to characterize therapeutic proteins in different formulations. In this work, we share a study on a diverse group of proteins, including their primary sequences, purity data, and computational and biophysical characterization at different pH and ionic strength. We report weak linear correlations between many of the biophysical parameters. We suggest that a stability comparison of diverse therapeutic protein candidates should be based on a computational and biophysical characterization in multiple formulation conditions, as the latter can largely determine whether a protein is above or below a certain stability threshold. We use the presented data set to calculate several stability risk scores obtained with an increasing level of analytical effort and show how they correlate with protein aggregation during storage. Our work highlights the importance of developing combined risk scores that can be used for early stage developability assessment. We suggest that such scores can have high prediction accuracy only when they are based on protein stability characterization in different solution conditions.