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Thinking outside the Laboratory: Analyses of Antibody Structure and Dynamics within Different Solvent Environments in Molecular Dynamics (MD) Simulations

机译:在实验室外思考:在分子动力学(MD)模拟中分析不同溶剂环境中的抗体结构和动力学

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摘要

Monoclonal antibodies (mAbs) have revolutionized the biomedical field, directly influencing therapeutics and diagnostics in the biopharmaceutical industry, while continuing advances in computational efficiency have enabled molecular dynamics (MD) simulations to provide atomistic insight into the structure and function of mAbs. Despite the success of MD tools, further optimizations are still required to enhance the computational efficiency of complex mAb simulations. This issue can be tackled by changing the way the solvent system is modelled to reduce the number of atoms to be tracked but must be done without compromising the accuracy of the simulations. In this work, the structure of the IgG2a antibody was analyzed in three solvent systems: explicit water and ions, implicit water and ions, and implicit water and explicit ions. Root-mean-square distance (RMSD), root-mean-square fluctuations (RMSF), and interchain angles were used to quantify structural changes. The explicit system provides the most atomistic detail but is ~6 times slower in its exploration of configurational space and required ~4 times more computational time on our supercomputer than the implicit simulations. Overall, the behavior of the implicit and explicit simulations is quantifiably similar, with the inclusion of explicit ions in the implicit simulation stabilizing the antibody to reproduce well the statistical fluctuations of the fully explicit system. Therefore, this approach holds promise to maximize the use of computational resources to explore antibody behavior.
机译:单克隆抗体(mAb)彻底改变了生物医学领域,直接影响了生物制药行业中的治疗和诊断,而计算效率的不断提高使分子动力学(MD)模拟能够提供有关mAbs结构和功能的原子学见解。尽管MD工具取得了成功,但仍需要进一步的优化来提高复杂mAb模拟的计算效率。可以通过更改溶剂系统的建模方式以减少要跟踪的原子数来解决此问题,但是必须在不影响模拟精度的情况下进行。在这项工作中,在两种溶剂系统中分析了IgG2a抗体的结构:显性水和离子,隐性水和离子以及隐性水和显性离子。均方根距离(RMSD),均方根波动(RMSF)和链间角度用于量化结构变化。显式系统提供了最多的原子细节,但对配置空间的探索要慢约6倍,并且在超级计算机上的计算时间比隐式模拟要慢约4倍。总体而言,隐式和显式模拟的行为在数量上相似,隐式模拟中包含显式离子可稳定抗体,从而很好地再现完全显式系统的统计波动。因此,该方法有望最大程度地利用计算资源来探索抗体行为。

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