This competing renewal application is devoted to the continued development and application of a unique and powerful multiscale computational approach to describe membranes and membrane processes. The project involves the rigorous bridging of scales using a "bottom-up" approach that is capable of translating molecular scale behavior into emergent mesoscopic scale phenomena. Extensive atomistic molecular dynamics simulations, along with novel enhanced sampling methods, are utilized to systematically develop powerful and thermodynamically consistent multiscale coarse-grained (MS-CG) models at the desired level of resolution. The MS-CG approach, which was a key breakthrough during the last funding period and is several orders of magnitude more computationally efficient than all-atom simulations, is in turn used to systematically construct mesoscopic simulation models in a multiscale fashion. The latter models allow for even larger length and time scale membrane phenomena to be accurately simulated.
The Specific Aims of this project are:
(Aim 1) the continued development of the transformative multiscale simulation methodology for the description of realistic heterogeneous membranes and membrane bound proteins, with a goal of making computer simulation more directly relevant to the fluid mosaic picture of real biological membranes;
(Aim 2) the application of the multiscale simulation methodology to large scale membrane remodeling phenomena, driven by BAR domain and ENTH domain protein modules, in close collaboration with experimentalists;
and (Aim 3) the application of mixed resolution all-atom/coarse-grained simulation methods to the membrane binding and aggregation of the matrix domain (MA) of the HIV-1 Gag polyprotein and the mechanosensitive channel of large conductance (MscL), again in collaboration and close contact with experimental research. The overarching long term goal of this project is to develop and apply a powerful, systematic, and rigorous multiscale computational approach to the study of biologically realistic membranes and membrane protein associated phenomena.

Public Health Relevance

Statement The project concerns the development and application of novel multiscale computer simulation methods for biomembrane systems. The target systems to be studied play a role in rare neurologic autoimmune disease, paraneoplastic Stiff-Man syndrome with breast cancer, Alzheimer's disease, Huntington's disease, pyogenic arthritis, influenza virus entry, the physiological basis for hearing, proprioception, and osmotic regulation, and the late stage of HIV-1 virus replication.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Chin, Jean
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University of Chicago
Schools of Arts and Sciences
United States
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Li, Jianing; Ziemba, Brian P; Falke, Joseph J et al. (2014) Interactions of protein kinase C-? C1A and C1B domains with membranes: a combined computational and experimental study. J Am Chem Soc 136:11757-66
Ziemba, Brian P; Li, Jianing; Landgraf, Kyle E et al. (2014) Single-molecule studies reveal a hidden key step in the activation mechanism of membrane-bound protein kinase C-?. Biochemistry 53:1697-713
Chen, Yolande; Aardema, Jorie; Kale, Sayali et al. (2013) Loss of the F-BAR protein CIP4 reduces platelet production by impairing membrane-cytoskeleton remodeling. Blood 122:1695-706
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Simunovic, Mijo; Mim, Carsten; Marlovits, Thomas C et al. (2013) Protein-mediated transformation of lipid vesicles into tubular networks. Biophys J 105:711-9
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Cui, Haosheng; Mim, Carsten; Vazquez, Francisco X et al. (2013) Understanding the role of amphipathic helices in N-BAR domain driven membrane remodeling. Biophys J 104:404-11
Mim, Carsten; Cui, Haosheng; Gawronski-Salerno, Joseph A et al. (2012) Structural basis of membrane bending by the N-BAR protein endophilin. Cell 149:137-45
Lyman, Edward; Cui, Haosheng; Voth, Gregory A (2011) Reconstructing protein remodeled membranes in molecular detail from mesoscopic models. Phys Chem Chem Phys 13:10430-6

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