Iourarum / GOPY

23 stars 18 forks source link

Looking for Graphene tutorial? Check out the file: Tutorial_GO_topology !

Update: I did a quick update recently. Personally I've been using GOPY for producing PDB files which I later imported into xleap / AmberTools. When it comes to graphene oxide (GO), an epoxy group contains two carbon atoms and both were given the same name in GOPY, "CY". I recently found that giving the second a different name worked better, so now the second is named "CZ". If you would like both of them to be "CY", either change the code or open a text editor and change all "CZ" to "CY". I will be perfectting this later (checking for errors etc). I did this because when I used xleap, I defined a lib file for the graphene atom, COOH residue, epoxy residue and hydroxyl residue and the "bondbydistance" command worked better this way. If you need help, have any question or are looking for a colaboration, please write to me at sebmuraru@gmail.com . I am willing to help! Also, please check my researchgate profile at: https://www.researchgate.net/profile/Sebastian_Muraru .

!!!IMPORTANT: if you encounter an error on line 2377, try adding

!/usr/bin/python
-- coding: latin-1 -\-

at the beginning of the code! (Thanks to Dr. Julio M. Coll, Dr. Biologia. Universidad Comlutense, Madrid, SPAIN)

GOPY_COO.py should allow one to add COO groups instead of COOH. Works identically.

GOPY: A tool for building 2D graphene-based computational models

Paper available at: https://doi.org/10.1016/j.softx.2020.100586

GOPY is a free and open-source Python tool written in order to automate the generation of 2D graphene-based molecular models such as pristine graphene (PG), together with different forms of graphene oxide (GO/ rGO/ GO-COOH/ GO-OH/ rGO-PEG-NH2 / N-doped graphene). Key advantages to using GOPY instead of manually building the molecular models are: significantly speeding up the process, reducing potential bias due to the manual placing of functional groups and facilitating the generation of much larger and more complex models than are usually built manually. Each model is outputted in the PDB format which is easily convertible to a wide array of other molecular formats.

Requires Python 3, numpy and scipy.

Quick Start

You can use GOPY in the following manner to generate graphene-based 2D PDB models:

python GOPY.py generate_PG X Y file_to_save
python GOPY.py generate_GO path_to_file X Y Z file_to_save
python GOPY.py generate_rGO_PEG_NH2 path_to_file X Y Z file_to_save
python GOPY.py generate_hole path_to_file N R1 R2 ARG1 ARG2 C file_to_save
python GOPY.py generate_N_doped path_to_file 10 9 8 file_to_save

Illustrative Examples

Illustrative Examples

Acknowledgements

This work was supported by a grant of the Ministry of Research and Innovation, Operational Program Competitiveness Axis 1—Section E, Program co-financed from European Regional Development Fund under the project number 154/25.11.2016, P_37_221/2015, “A novel graphene biosensor testing osteogenic potency; capturing best stem cell performance for regenerative medicine” (GRABTOP).

Please cite us:

https://doi.org/10.1016/j.softx.2020.100586