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arXiv 2408.01407cond-mat.softphysics.chem-phq-bio.BM
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基于动态无偏分子动力学模拟研究脂质双层中跨膜二聚化的自由能、速率与机制

Free energy, rates, and mechanism of transmembrane dimerization in lipid bilayers from dynamically unbiased molecular dynamics simulations

Emil Jackel, Gianmarco Lazzeri, Roberto Covino

AI总结:

本文提出一种仅依赖短时动态无偏轨迹片段、无需集体变量或偏置力的新算法,可在同一组模拟中同时获得跨膜二聚化的自由能曲线、速率和机制,并在 Martini 力场下验证了其有效性。

摘要:

蛋白质在膜中的组装在许多关键细胞通路中发挥着重要作用。尽管其重要性不言而喻,但表征跨膜组装过程对实验和模拟而言仍具有挑战性。平衡分子动力学模拟无法覆盖采样典型跨膜组装所需的时间尺度。因此,大多数研究依赖于增强采样方案,这些方案沿着一个应编码所有慢自由度的集体变量来引导跨膜蛋白的动力学。然而,鉴于凝聚相脂质环境的复杂性,这远非易事,其后果是二聚化的自由能曲线可能收敛不佳。在此,我们引入一种替代方法,该方法仅依赖于模拟短的、动态无偏的轨迹片段,避免使用集体变量或偏置力。通过合并所有轨迹,我们利用同一组模拟即可获得跨膜二聚化的自由能曲线、速率和机制。我们通过采样脂质双层中跨膜蛋白的自发结合与解离来展示我们的算法,使用的是广泛采用的粗粒度 Martini 力场。我们的算法为研究生物学相关膜中的组装过程提供了一种有前景的途径,克服了传统方法的一些挑战。

英文摘要:

The assembly of proteins in membranes plays a key role in many crucial cellular pathways. Despite their importance, characterizing transmembrane assembly remains challenging for experiments and simulations. Equilibrium molecular dynamics simulations do not cover the time scales required to sample the typical transmembrane assembly. Hence, most studies rely on enhanced sampling schemes that steer the dynamics of transmembrane proteins along a collective variable that should encode all slow degrees of freedom. However, given the complexity of the condensed-phase lipid environment, this is far from trivial, with the consequence that free energy profiles of dimerization can be poorly converged. Here, we introduce an alternative approach, which relies only on simulating short, dynamically unbiased trajectory segments, avoiding using collective variables or biasing forces. By merging all trajectories, we obtain free energy profiles, rates, and mechanisms of transmembrane dimerization with the same set of simulations. We showcase our algorithm by sampling the spontaneous association and dissociation of a transmembrane protein in a lipid bilayer, the popular coarse-grained Martini force field. Our algorithm represents a promising way to investigate assembly processes in biologically relevant membranes, overcoming some of the challenges of conventional methods.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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