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Conformational Ensembles of Antibodies Determine Their Hydrophobicity
Biophysical Journal ( IF 3.4 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.bpj.2020.11.010
Franz Waibl 1 , Monica L Fernández-Quintero 1 , Anna S Kamenik 1 , Johannes Kraml 1 , Florian Hofer 1 , Hubert Kettenberger 2 , Guy Georges 2 , Klaus R Liedl 1
Affiliation  

A major challenge in the development of antibody biotherapeutics is their tendency to aggregate. One root cause for aggregation is exposure of hydrophobic surface regions to the solvent. Many current techniques predict the relative aggregation propensity of antibodies via pre-calculated scales for the hydrophobicity or aggregation propensity of single amino acids. However, those scales cannot describe the non-additive effects of a residue's surrounding on its hydrophobicity. Therefore, they are inherently limited in their ability to describe the impact of subtle differences in molecular structure on the overall hydrophobicity. Here, we introduce a physics-based approach to describe hydrophobicity in terms of the hydration free energy using Grid Inhomogeneous Solvation Theory (GIST). We apply this method to assess the effects of starting structures, conformational sampling, and protonation states on the hydrophobicity of antibodies. Our results reveal that high-quality starting structures, i.e., crystal structures, are crucial for the prediction of hydrophobicity and that conformational sampling can compensate errors introduced by the starting structure. On the other hand, sampling of protonation states only leads to good results when combined with high-quality structures, while it can even be detrimental otherwise. We conclude by pointing out that a single static homology model may not be adequate for predicting hydrophobicity.

中文翻译:

抗体的构象集合决定了它们的疏水性

抗体生物治疗药物开发的一个主要挑战是它们的聚集趋势。聚集的一个根本原因是疏水表面区域暴露于溶剂。许多当前技术通过预先计算的单个氨基酸的疏水性或聚集倾向的尺度来预测抗体的相对聚集倾向。然而,这些尺度不能描述残基周围对其疏水性的非累加效应。因此,它们在描述分子结构的细微差异对整体疏水性的影响方面存在固有的局限性。在这里,我们介绍了一种基于物理的方法,使用网格非均匀溶剂化理论 (GIST) 根据水合自由能来描述疏水性。我们应用这种方法来评估起始结构、构象采样和质子化状态对抗体疏水性的影响。我们的结果表明,高质量的起始结构,即晶体结构,对于预测疏水性至关重要,并且构象采样可以补偿起始结构引入的误差。另一方面,质子化状态的采样只有在与高质量结构结合时才能产生良好的结果,否则甚至可能是有害的。我们最后指出,单个静态同源模型可能不足以预测疏水性。对于疏水性的预测至关重要,并且构象采样可以补偿由起始结构引入的误差。另一方面,质子化状态的采样只有在与高质量结构结合时才能产生良好的结果,否则甚至可能是有害的。我们最后指出,单个静态同源模型可能不足以预测疏水性。对于疏水性的预测至关重要,并且构象采样可以补偿由起始结构引入的误差。另一方面,质子化状态的采样只有在与高质量结构结合时才能产生良好的结果,否则甚至可能是有害的。我们最后指出,单个静态同源模型可能不足以预测疏水性。
更新日期:2021-01-01
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