SYSTEMATIC COARSE-GRAINING OF LIPID BILAYERS WITH IMPLICIT SOLVENT

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 脂双层是所有活细胞的关键结构成分之一。它们将细胞生化环境划分并组织成细胞器，并在调节物质和信号在空间分离区域之间的受控传输中发挥关键作用。而不是像人们一直认为的那样，仅仅溶解膜蛋白，我们现在知道，脂双层积极参与了许多这样的细胞活动，这重新引起了人们对其生物物理和材料特性的兴趣。然而，当前研究关注的许多事件--囊泡、分选、内吞、感觉、运动等--发生在长度和相关的时间尺度上，这远远超出了原子分子模拟技术的能力范围。因此，人们对开发粗粒度模型非常感兴趣，这种模型可以减少所需自由度的数量，并能够对在很大程度上独立于化学细节的现象进行系统研究[1]。其中，不需要包埋溶剂的模型最有希望最终弥合细胞器水平的差距[2]，但它们仍然是模拟工具箱中最新的成员，需要进一步研究。PI最近开发了一个高度粗粒度的无溶剂脂类模型[3]，并成功地将其应用于涉及组成-曲率耦合[4]和曲率介导的相互作用[5]的问题。虽然它有力地代表了大规模的膜特性，但它还没有足够精细地解决与脂蛋白相互作用的几个方面有关的结构双层细节。为了弥补这一差距，更详细地描述脂类，PI建议谨慎地重新引入自由度和脂类物种个性，同时保持包埋溶剂的隐含。我们的计划是遵循一种基于结构的粗粒化(或细粒化)技术，将现有的原子和介观尺度连接到无溶剂领域。这种方法尤其需要强大的计算能力，才能在更精细的细节水平上获得非常好的结构统计数据，因此有必要使用超级计算设施。在DAC框架内分配的CPU时间既将作为初始系统启动，更重要的是，有助于获得制定后续MRAC提案所需的关键经验和扩展信息。[1]M.Muller、K.Katsov和M.Schick，《生物和合成膜：从粗粒度描述中可以学到什么？》，Phys。Rep.434_，113(2006)；M.Venturoli、M.M.Sperotto、M.Kranenburg和B.Smit，“生物膜的介观模型”，Phys.代表_437_，1(2006)[2]G.Brannigan、L.C.L.Lin和F.L.H.Brown，《用于生物膜的隐式溶剂模拟模型》，EUR.生物群落。J._35_，104(2006)。[3]I.R.Cooke、K.Kremer和M.Desno，《流体双层膜的可调谐通用模型》，Phys.Rev.E_72_，011506(2005年)；I.R.Cooke和M.Disno，“自组装流体双层膜的无溶剂模型：基于广泛吸引尾势的流体相的稳定”，J.化学。太棒了。_123_，224710(2005年)。[4]I.R.Cooke和M.Disno，“脂质形状和膜曲率之间的耦合”，生物物理学。J._91_，487(2006)。[5]B.J.Reynwar、G.Illya、V.A.Harmandaris、M.M.Muller、K.Kremer和M.Disno，“通过曲率调节相互作用的膜蛋白的聚集和囊泡形成”，Nature_447_，461-464(2007)。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Lipid bilayers are one of the key structural components of all living cells. They compartmentalize and organize the cellular biochemical environment into organelles and play a key role in mediating controlled transport of substances and signals between spatially separated domains. Rather than merely solubilizing membrane proteins, as has long been believed, we now know that lipid bilayers actively participate in many of these cellular events, and this has generated a renewed interest in their biophysical and material characteristics. However, many of the events on which current research focuses -- vesiculation, sorting, endocytosis, sensing, locomotion, etc. -- occur on length- and associated time-scales which are significantly beyond the reach of atomistic molecular simulation techniques. Hence, much interest has been devoted to the development of coarse-grained models that reduce the number of required degrees of freedom and enable the systematic studies of phenomena which are largely independent of chemical detail [1]. Among them, models that eliminate the need for an embedding solvent hold the largest promise to finally bridge the gap to the organelle level [2], but they are still a very recent addition to the simulation toolbox and require further studies. The PI has recently developed a highly coarse-grained solvent-free lipid model [3] and successfully applied it to problems involving composition-curvature coupling [4] and curvature-mediated interactions [5]. While robustly representing large-scale membrane properties, it is not finely enough resolved to account for structural bilayer detail that matters for several aspects of lipid-protein interactions. In order to bridge the gap backwards to more detailed descriptions of lipids, the PI proposes to carefully reintroduce degrees of freedom and lipid species individuality, while at the same time keeping the embedding solvent implicit. The plan is to follow a structure-based coarse- (or fine-) graining technique which links existing atomistic and mesoscopic scales to the solvent free realm. Such an approach will in particular require significant computational power to obtain very good structural statistics on the finer levels of detail, thus necessitating the access to supercomputing facilities. The CPU time awarded within the framework of a DAC will both serve as an initial system startup and -- more importantly -- help to gain crucial experience and scaling information required to formulate a subsequent MRAC proposal. [1] M. Muller, K. Katsov, and M. Schick, "Biological and synthetic membranes: What can be learned from a coarse-grained description?", Phys. Rep. _434_, 113 (2006); M. Venturoli, M.M. Sperotto, M. Kranenburg, and B. Smit, "Mesoscopic models of biological membranes", Phys. Rep. _437_, 1 (2006). [2] G. Brannigan, L.C.L. Lin, and F.L.H Brown, "Implicit solvent simulation models for biomembranes", Eur. Biophys. J. _35_, 104 (2006). [3] I.R. Cooke, K. Kremer, and M. Deserno, "Tunable generic model for fluid bilayer membranes", Phys. Rev. E _72_, 011506 (2005); I.R. Cooke and M. Deserno, "Solvent-free model for self-assembling fluid bilayer membranes: Stabilization of the fluid phase based on broad attractive tail potentials", J. Chem. Phys. _123_, 224710 (2005). [4] I.R. Cooke and M. Deserno, "Coupling between lipid shape and membrane curvature", Biophys. J. _91_, 487 (2006). [5] B.J. Reynwar, G. Illya, V.A. Harmandaris, M.M. Muller, K. Kremer, and M. Deserno, "Aggregation and vesiculation of membrane proteins by curvature-mediated interactions", Nature _447_, 461-464 (2007).