Analysis Techniques


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<h2>Initial Steps and Analysis</h2> <blockquote> <p>First make sure your file organization system mirrors mine, here. - All xtc files for a given replicate are either in the MDrun/replicate directory or an MDrun/replicate/timeframe - You are operating the analysis submission script from an analysis folder, MDrun/replicate/protein_analysis - You have put the additional scripts provided inside of a folder inside of the analysis folder and named it scripts, i. e. MDrun/replicate/protein_analysis/scripts</p> <p><a href="" rel="nofollow">Learn More</a></p> </blockquote> <h2>Distance Between Regions</h2> <blockquote> <p>Purpose: Use Gromacs to see the distance of two regions from one another over time. Similar analysis may be applied to two residues, or perhaps even atoms or systems involving multiple peptides. Why is this useful you ask? Often distances between regions are characteristic of conformational changes indicative of ligand binding or activity/inactivity (Think Helm: R and T states). <a href="" rel="nofollow">Learn More</a></p> </blockquote> <h2>Direct ID and Eigenvectors ##</h2> <p><a href="" rel="nofollow">Learn More</a></p> <h2>MD Movie (TBC)</h2> <p><a href="" rel="nofollow">Learn More</a></p> <h2>RMSD Block Averaging ##</h2> <blockquote> <p>Purpose: To check for convergence! This method is much more quantitative and therefore robust than observing an RMSD graph. Essentially, you will break the RMSD down into segments, average the RMSD in each segment (block), and see if it changes over time. The standard deviation of each block is indicative of fluctuation, and if converged, each block should be relatively the same (see table at the bottom for an example of a converged run). <a href="" rel="nofollow">Learn More</a></p> </blockquote>
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