Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland Baltimore, Baltimore, Maryland 21201, United States.
SilcsBio LLC, 1100 Wicomico Street, Suite 323, Baltimore, Maryland 21230, United States.
Mol Pharm. 2023 May 1;20(5):2600-2611. doi: 10.1021/acs.molpharmaceut.3c00064. Epub 2023 Apr 5.
Protein-based therapeutics typically require high concentrations of the active protein, which can lead to protein aggregation and high solution viscosity. Such solution behaviors can limit the stability, bioavailability, and manufacturability of protein-based therapeutics and are directly influenced by the charge of a protein. Protein charge is a system property affected by its environment, including the buffer composition, pH, and temperature. Thus, the charge calculated by summing the charges of each residue in a protein, as is commonly done in computational methods, may significantly differ from the effective charge of the protein as these calculations do not account for contributions from bound ions. Here, we present an extension of the structure-based approach termed site identification by ligand competitive saturation-biologics (SILCS-Biologics) to predict the effective charge of proteins. The SILCS-Biologics approach was applied on a range of protein targets in different salt environments for which membrane-confined electrophoresis-determined charges were previously reported. SILCS-Biologics maps the 3D distribution and predicted occupancy of ions, buffer molecules, and excipient molecules bound to the protein surface in a given salt environment. Using this information, the effective charge of the protein is predicted such that the concentrations of the ions and the presence of excipients or buffers are accounted for. Additionally, SILCS-Biologics also produces 3D structures of the binding sites of ions on the proteins, which enable further analyses such as the characterization of protein surface charge distribution and dipole moments in different environments. Notable is the capability of the method to account for competition between salts, excipients, and buffers on the calculated electrostatic properties in different protein formulations. Our study demonstrates the ability of the SILCS-Biologics approach to predict the effective charge of proteins and its applicability in uncovering protein-ion interactions and their contributions to protein solubility and function.
蛋白质类治疗药物通常需要高浓度的活性蛋白，这可能导致蛋白聚集和溶液高黏度。这些溶液行为会限制蛋白质类治疗药物的稳定性、生物利用度和可制造性，并且直接受蛋白电荷的影响。蛋白电荷是一个受环境影响的系统特性，包括缓冲液组成、pH 值和温度。因此，如计算方法中通常所做的那样，通过对蛋白中每个残基的电荷求和来计算的电荷，可能与蛋白的有效电荷显著不同，因为这些计算未考虑结合离子的贡献。在这里，我们提出了一种基于结构的方法的扩展，即配体竞争饱和-生物大分子（SILCS-Biologics），用于预测蛋白的有效电荷。SILCS-Biologics 方法应用于一系列不同盐环境下的蛋白靶标，这些蛋白靶标先前已报道有膜限制电泳测定的电荷。SILCS-Biologics 方法绘制了在给定盐环境下与蛋白表面结合的离子、缓冲分子和赋形剂分子的 3D 分布和预测占有率。利用这些信息，预测蛋白的有效电荷，以考虑离子浓度和赋形剂或缓冲液的存在。此外，SILCS-Biologics 还产生了蛋白上离子结合位点的 3D 结构，这使得可以进行进一步的分析，例如不同环境下蛋白表面电荷分布和偶极矩的特征化。值得注意的是，该方法能够在不同的蛋白配方中，考虑盐、赋形剂和缓冲液之间的竞争，对计算静电性质的影响。我们的研究证明了 SILCS-Biologics 方法预测蛋白有效电荷的能力，以及它在揭示蛋白-离子相互作用及其对蛋白溶解度和功能的贡献方面的适用性。
