کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5532877 1402084 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
SimGen: A General Simulation Method for Large Systems
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی بیولوژی سلول
پیش نمایش صفحه اول مقاله
SimGen: A General Simulation Method for Large Systems
چکیده انگلیسی

SimGen is a stand-alone computer program that reads a script of commands to represent complex macromolecules, including proteins and nucleic acids, in a structural hierarchy that can then be viewed using an integral graphical viewer or animated through a high-level application programming interface in C++.Structural levels in the hierarchy range from α-carbon or phosphate backbones through secondary structure to domains, molecules, and multimers with each level represented in an identical data structure that can be manipulated using the application programming interface. Unlike most coarse-grained simulation approaches, the higher-level objects represented in SimGen can be soft, allowing the lower-level objects that they contain to interact directly.The default motion simulated by SimGen is a Brownian-like diffusion that can be set to occur across all levels of representation in the hierarchy. Links can also be defined between objects, which, when combined with large high-level random movements, result in an effective search strategy for constraint satisfaction, including structure prediction from predicted pairwise distances.The implementation of SimGen makes use of the hierarchic data structure to avoid unnecessary calculation, especially for collision detection, allowing it to be simultaneously run and viewed on a laptop computer while simulating large systems of over 20,000 objects. It has been used previously to model complex molecular interactions including the motion of a myosin-V dimer “walking” on an actin fibre, RNA stem-loop packing, and the simulation of cell motion and aggregation. Several extensions to this original functionality are described.

Graphical Abstract319

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Molecular Biology - Volume 429, Issue 3, 3 February 2017, Pages 408-415
نویسندگان
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