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10.1016/j.jmgm.2016.05.001

http://scihub22266oqcxt.onion/10.1016/j.jmgm.2016.05.001
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C5954827!5954827!27179343
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suck abstract from ncbi

pmid27179343      J+Mol+Graph+Model 2016 ; 67 (ä): 44-53
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  • Visualizing ensembles in structural biology #MMPMID27179343
  • Melvin RL; Salsbury FR
  • J Mol Graph Model 2016[Jun]; 67 (ä): 44-53 PMID27179343show ga
  • Displaying a single representative conformation of a biopolymer rather than an ensemble of states mistakenly conveys a static nature rather than the actual dynamic personality of biopolymers. However, there are few apparent options due to the fixed nature of print media. Here we suggest a standardized methodology for visually indicating the distribution width, standard deviation and uncertainty of ensembles of states with little loss of the visual simplicity of displaying a single representative conformation. Of particular note is that the visualization method employed clearly distinguishes between isotropic and anisotropic motion of polymer subunits. We also apply this method to ligand binding, suggesting a way to indicate the expected error in many high throughput docking programs when visualizing the structural spread of the output. We provide several examples in the context of nucleic acids and proteins with particular insights gained via this method. Such examples include investigating a therapeutic polymer of FdUMP (5-fluoro-2-deoxyuridine-5-O-monophosphate) ? a topoisomerase-1 (Top1), apoptosis-inducing poison ? and nucleotide-binding proteins responsible for ATP hydrolysis from Bacillus subtilis. We also discuss how these methods can be extended to any macromolecular data set with an underlying distribution, including experimental data such as NMR structures.
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