在马提尼3力场中优化蛋白质-赋形剂相互作用

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Tobias M. Prass, Kresten Lindorff-Larsen, Patrick Garidel, Michaela Blech* and Lars V. Schäfer*, 
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引用次数: 0

摘要

生物治疗药物(如单克隆抗体(mAbs))所需的药物剂量高,而皮下注射给药量小,这给高浓度制剂带来了挑战。在高浓度蛋白质制剂中添加精氨酸和谷氨酸等辅料可以提高溶解度,减少蛋白质颗粒形成的趋势。分子动力学(MD)模拟可以从微观角度揭示 mAb 制剂中辅料的作用模式,但这需要较大的系统规模和较长的时间尺度,而目前的完全原子水平还无法实现。计算效率高的粗粒度模型(如 Martini 3 力场)可以应对这一挑战,但需要仔细的参数化、测试和验证。本研究以治疗用 mAbs 曲妥珠单抗和奥马珠单抗的 Fab 结构域为模型系统,将广受欢迎的 Martini 3 力场扩展到精氨酸和谷氨酸辅料的真实蛋白质-辅料相互作用。介绍了一种新的氨基酸辅料从全原子到粗粒度的映射,它明确捕捉到了骨架的齐聚物特性。精氨酸和谷氨酸的 Fab-辅料相互作用的特点是在单残基水平上与 Fab 发生分子接触。将 Martini 3 模拟结果与全原子模拟结果进行了比较。我们的研究结果表明,使用 Martini 3 的默认相互作用参数,Fab 与辅料的接触被高估了,这表明蛋白质残基与辅料之间的吸引力过强。因此,我们根据全原子模拟对 Martini 3 中的蛋白质-辅料相互作用参数进行了重新参数化。使用新的 Martini 3 绘图和伦纳德-琼斯(LJ)相互作用参数(合称 Martini 3-exc)得到的辅料相互作用与全原子参考数据非常吻合。这项研究提出了 Martini 3 粗粒度力场中 mAb-精氨酸和 mAb-谷氨酸相互作用的改进参数集,这是对高浓度 mAb 制剂和辅料稳定效应进行大规模粗粒度 MD 模拟的关键一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Optimized Protein–Excipient Interactions in the Martini 3 Force Field

Optimized Protein–Excipient Interactions in the Martini 3 Force Field

The high doses of drugs required for biotherapeutics, such as monoclonal antibodies (mAbs), and the small volumes that can be administered to patients by subcutaneous injections pose challenges due to high-concentration formulations. The addition of excipients, such as arginine and glutamate, to high-concentration protein formulations can increase solubility and reduce the tendency of protein particle formation. Molecular dynamics (MD) simulations can provide microscopic insights into the mode of action of excipients in mAb formulations but require large system sizes and long time scales that are currently beyond reach at the fully atomistic level. Computationally efficient coarse-grained models such as the Martini 3 force field can tackle this challenge but require careful parametrization, testing, and validation. This study extends the popular Martini 3 force field toward realistic protein–excipient interactions of arginine and glutamate excipients, using the Fab domains of the therapeutic mAbs trastuzumab and omalizumab as model systems. A novel all-atom to coarse-grained mapping of the amino acid excipients is introduced, which explicitly captures the zwitterionic character of the backbone. The Fab–excipient interactions of arginine and glutamate are characterized concerning molecular contacts with the Fabs at the single-residue level. The Martini 3 simulations are compared with results from all-atom simulations as a reference. Our findings reveal an overestimation of Fab–excipient contacts with the default interaction parameters of Martini 3, suggesting a too strong attraction between protein residues and excipients. Therefore, we reparametrized the protein–excipient interaction parameters in Martini 3 against all-atom simulations. The excipient interactions obtained with the new Martini 3 mapping and Lennard-Jones (LJ) interaction parameters, coined Martini 3-exc, agree closely with the all-atom reference data. This work presents an improved parameter set for mAb-arginine and mAb-glutamate interactions in the Martini 3 coarse-grained force field, a key step toward large-scale coarse-grained MD simulations of high-concentration mAb formulations and the stabilizing effects of excipients.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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