Optimized Protein-Excipient Interactions in the Martini 3 Force Field.

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2025-04-14 Epub Date: 2025-03-24 DOI:10.1021/acs.jcim.4c02338
Tobias M Prass, Kresten Lindorff-Larsen, Patrick Garidel, Michaela Blech, Lars V Schäfer
{"title":"Optimized Protein-Excipient Interactions in the Martini 3 Force Field.","authors":"Tobias M Prass, Kresten Lindorff-Larsen, Patrick Garidel, Michaela Blech, Lars V Schäfer","doi":"10.1021/acs.jcim.4c02338","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":" ","pages":"3581-3592"},"PeriodicalIF":5.3000,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Information and Modeling ","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.jcim.4c02338","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/24 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0

Abstract

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
在马提尼3力场中优化蛋白质-赋形剂相互作用。
单克隆抗体(mab)等生物疗法所需的高剂量药物,以及可通过皮下注射给患者的小体积药物,由于配方的高浓度,给患者带来了挑战。在高浓度蛋白质制剂中加入精氨酸和谷氨酸等辅料,可以增加溶解度,降低蛋白质颗粒形成的倾向。分子动力学(MD)模拟可以提供单抗制剂中赋形剂作用模式的微观洞察,但需要大系统尺寸和长时间尺度,目前在完全原子水平上无法达到。计算效率高的粗粒度模型(如Martini 3力场)可以解决这一挑战,但需要仔细的参数化、测试和验证。本研究将流行的Martini 3力场扩展到精氨酸和谷氨酸赋形剂的实际蛋白质-赋形剂相互作用,使用治疗性单抗曲妥珠单抗和奥玛珠单抗的Fab结构域作为模型系统。介绍了一种新的氨基酸赋形剂的全原子到粗粒度映射,它明确地捕获了主链的两性离子特征。精氨酸和谷氨酸的fab -赋形剂相互作用的特征是在单残基水平上与fab的分子接触。作为参考,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,在马提尼3的默认相互作用参数下,对fab -赋形剂接触的估计过高,表明蛋白质残基和赋形剂之间的吸引力太强。因此,我们针对全原子模拟,重新参数化了Martini 3中蛋白质-赋形剂相互作用参数。用新的Martini 3映射和Lennard-Jones (LJ)相互作用参数(称为Martini 3-exc)得到的赋形剂相互作用与全原子参考数据基本一致。本研究提出了一种改进的mAb-精氨酸和mAb-谷氨酸在Martini 3粗粒度力场中相互作用的参数集,这是对高浓度mAb配方进行大规模粗粒度MD模拟和辅料稳定效应的关键一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
DeepMIF: A Multiview Interactive Fusion-Based Deep Learning Method for RNA–Small Molecule Binding Affinity Prediction SGLEPocket: A Spatial Gating and Local Feature Enhancement Network for Protein–Ligand Binding Pocket Prediction Exploring Secondary Structure Predictions for RNA-Targeted Drug Discovery: Power and Challenges Unveiling the Activation Mechanism of Glucagon-Like Peptide-1 Receptor by an Ago-Allosteric Modulator via Molecular Dynamics Simulations ProtCross: Bridging the PDB-AlphaFold Gap for Binding Site Prediction with Protein Point Clouds.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1