This repository provides a standalone Python3 implementation of the NapShift-CG (CG: Coarse Grain) program to estimate the backbone atoms' chemical shift values from martinized PBD files. It is based on the published and tested NapShift program that works on full atomistic proteins. For more information have a look at NapShift.
M. Vrettas, PhD.
Here is presented a comparison of the RMSD, in ppm, between the original NapShift predicted
chemical shifts (CS) and a set of experimental CS (from 250 test proteins) for varying input
peptide lengths (1, 3, 5, and 7) to the NapShift.

Below is presented the same comparison as above using the reduced NapShift-CG predicted
chemical shifts (CS) and the experimental CS (on the same test proteins), for varying input
peptide lengths (1, 3, 5, and 7) to the NapShift-CG.

There are two options to install the software.
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The easiest way is to visit the GitHub web-page of the project and download the code in zip format. This option does not require a prior installation of git on the computer.
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Alternatively one can clone the project directly using git as follows:
git clone https://github.com/vrettasm/NapShift_CG.git
The minimum version is Python 3.7 (recommended >=3.8). The required packages are given in the "requirements.txt": To simplify the installation of the packages just use:
pip install -r requirements.txt
It is highly advised to create a separate virtual environment to avoid messing with the main Python installation. On Linux and macOS systems type:
python3 -m venv napshift_cg_venv
Note: "napshift_cg_venv" is an optional name.
Once the virtual environment is created activate it with:
source napshift_cg_venv/bin/activate
Make sure pip is updated:
python3 -m pip install --upgrade pip
Then we can install all the requirements as above:
pip install -r requirements.txt
or
python3 -m pip install -r requirements.txt
N.B. For Windows systems follow the equivalent instructions.
To execute the program (within the activated virtual environment), you can either navigate to the main directory of the project (i.e. where the napshift_cg.py is located), or locate it through the command line and then run the following command:
./napshift_cg.py -f path/to/filename.pdb
This is the simplest way to run NapShift. It will create a file named: "prediction_filename_model_0_chain_A.tab" in the current working directory, with the predicted chemical shift values for all backbone atoms (N, C, Ca, Cb, H, Ha).
Hint: If you want to run the program on multiple files (in the same directory) you can use the '*' wildcard as follows:
$ ./napshift_cg.py -f path/to/*.pdb
This will run NapShift on all the files (in the directory) with the '.pdb' extension.
To explore all the options of NapShift, use:
./napshift_cg.py -h
You will see the following menu:
For any questions/comments (regarding this code) please contact me at: vrettasm@gmail.com

