Collaborative Research: Multiscale Methods for the Molecular Simulation of Sensory Mechanotransduction Channels
Collaborative Research: Multiscale Methods for the Molecular Simulation of Sensory Mechanotransduction Channels
批准号:
0718349
负责人:
Eric Darve
金额:
$25.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-09-01 至 2010-08-31
中文摘要
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英文摘要
This research will create new mathematical and numerical methods to study the dynamics of large proteins found in touch sensory neurons of C. elegans, a worm with one of the simplest touch sensory nervous system. The main issues are bridging the gap between relevant biological time scales, in this case the opening and closing of ion channels, and time scales accessible to direct molecular dynamics simulations which are much shorter. A step in this direction will be the creation of a new time and space adaptive scheme (AVI and HiGrid) which accelerates the sampling of the different protein conformations accessible at a given temperature. In addition, techniques (the string method and the ABF algorithm) to explore transition pathways between stable conformations of the system will be developed. The novelty of this approach is that the pathways are computed in terms of many collective variables instead of the Cartesian coordinates of the atoms as is usually done. This leads to greater robustness and physically more relevant pathways.The ability to sense touch depends on nanometer sized ion channels located in the membrane of sensory neurons. When force is exerted in the skin these channels open to let a flow of ions go in or out of the cell, a phenomenon called gating. These nano-machines are part of a complex apparatus which converts mechanical force into electric signals and transports information from the skin to neurons. By bringing together expertise in biology, high performance computing and mathematics, the investigators will produce atomically accurate models of the gating mechanism in the only metazoan mechanotransduction channel known to date.
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Large-scale stochastic inverse and data assimilation problems with applications to subsurface imaging
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资助金额:$70.0万
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财政年份:2012
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负责人:Eric Darve
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依托单位:
国内基金
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