Enhanced Sampling Reveals Metastable Conformations Driving K417N-Mediated Class I Antibody Escape.

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Xu Pan,Takashi Tadokoro,Taishi Onodera,Shunsuke Kita,Yoshimasa Takahashi,Katsumi Maenaka,Hisham M Dokainish
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Abstract

The continuous emergence of SARS-CoV-2 variants compromises the effectiveness of neutralizing antibodies (nAbs), contributing to immune evasion. Several single-point mutations in the receptor-binding domain (RBD) have been shown to drastically affect the recognition of Class I antibodies. Understanding the molecular mechanisms behind such single-point mutations remains challenging, especially as weak binding affinity prevents the characterization of complex structures through conventional experimental methods. Here, we employ enhanced sampling molecular dynamics (MD) simulations, the generalized replica exchange with solute tempering (gREST), to investigate the structural and dynamic impacts of the K417N mutation on NT-193 (Class I) binding to RBD. Although stable conformations of wild-type and mutants show similar binding interactions, the mutation profoundly reshapes the transient metastable states. At the key interface between the heavy and light chains, the substitution of lysine with asparagine disrupts key interactions with the heavy chain in metastable states, facilitating antibody dissociation. Consistent with simulation results, surface plasmon resonance (SPR) experiments confirm that K417N significantly increases the dissociation rate, reducing the overall binding affinity to RBD. These findings illustrate the importance of capturing metastable conformations to fully understand mutation-driven immune evasion mechanisms. Moreover, this study demonstrates the power of applying gREST to unravel essential insights into transient and weakly interacting antibody-antigen complexes, facilitating the rational design and optimization of next-generation antibody therapeutics capable of overcoming viral immune escape.
增强采样揭示亚稳构象驱动k417n介导的I类抗体逃逸。
SARS-CoV-2变体的不断出现削弱了中和抗体(nab)的有效性,导致免疫逃避。受体结合域(RBD)的几个单点突变已被证明会极大地影响I类抗体的识别。理解这种单点突变背后的分子机制仍然具有挑战性,特别是弱结合亲和力阻碍了传统实验方法对复杂结构的表征。在这里,我们采用增强的采样分子动力学(MD)模拟,即溶质回火广义复制交换(gREST),来研究K417N突变对NT-193 (I类)与RBD结合的结构和动态影响。尽管野生型和突变型的稳定构象显示出相似的结合相互作用,但突变深刻地重塑了瞬时亚稳态。在重链和轻链之间的关键界面,赖氨酸被天冬酰胺取代破坏了与重链在亚稳态的关键相互作用,促进了抗体的解离。与模拟结果一致,表面等离子体共振(SPR)实验证实K417N显著增加了解离速率,降低了对RBD的整体结合亲和力。这些发现说明了捕获亚稳态构象对于充分理解突变驱动的免疫逃避机制的重要性。此外,该研究证明了应用gREST揭示瞬时和弱相互作用抗体-抗原复合物的基本见解的力量,促进了能够克服病毒免疫逃逸的下一代抗体疗法的合理设计和优化。
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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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