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'Fits' a vector/vectors to the helix/helicies using Singular Value Decomposition (SVD) and measures angle between them in a trajectory.

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Vikasdubey0551/svd_angle_between_vectors

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Description

The following script perform singular value decomposition (SVD) the chosen and extracts the fist eigenvector. This process mimics the process of 'fitting' a vector to 3D data or a 3D regression. This is particularly useful for measuring angle between two alpha helicies in a simulation dataset. Alternatively, it can also used to angle fluctuations with respect to a particular axis.

Prerequisite to the script are numpy, scipy and matplotlib (optional). The script can be directly modified for use.

Usage

  • Selection : First an appropriate part(s) of the protein needs to be selected to perform the calculation :

Examples

range of residues : e.g. selecting 100 to 120 residues => 'protein and resid 100:120'

range of atoms : e.g. selecting 2102 to 2485 residues => 'protein and bynum 2102:2485'

  • Choosing the files : choose the names of the files mda.Universe('step7_production.gro','step7_production.xtc'). Uncommment the plotting it is necessary.

  • Running the script : Python angle_estimator.py

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'Fits' a vector/vectors to the helix/helicies using Singular Value Decomposition (SVD) and measures angle between them in a trajectory.

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