The vast majority of the resources are in some type of text format, either as scripts or as type-formatted data files that, although compatible with standard Windows formats, were primarily made with (and used in) Unix/Unix-like OS environments (i.e. Linux and Mac OS). This means that in order to view them properly, you will need a text editor capable of properly reading text across different platforms, preferrably with options for syntax highlighting and scripting/programming language support. A good, freely available option for Windows is Notepad++. As far as Linux users are concerned, the default text editor in your distribution (gedit, nedit, leafpad, xed etc), as well as nano/pico and vi/vim (for terminal users) can do the trick, as they ussually have all the required features for coding/scripting and support virtually all text encoding options ever created. Mac OS users, finally, you’re on your own. Either try installing gedit for Mac or pay to buy a text editor in your Apple Store.
Force Field Parameters
Karplus Equation Calculator: Perl script that uses the Karplus equation to predict J-couplings based on dihedral angle calculations from MD simulation data, as produced by the GROMACS “gmx angle” utility. Useful for analyzing dihedral angle measurements of carbohydrate simulations.
Requirements: Perl 5.x (Not working with Perl 6/Raku)
Jarzynski Equality PMF calculator (Python 3.x version): A Python 3 script to perform Potential of Mean Force (PMF) calculations using Jarzynski’s equality, for pulling simulations generated by GROMACS. Useful for analyzing Steered Molecular Dynamics (SMD) simulation data and doing a “quick and dirty” estimation of a PMF, although it will never be as accurate as good old Umbrella Sampling or Free Energy Perturbations.
Requirements: Python 3.x (preferably 3.5 or higher)
Jarzynski Equality PMF calculator (Python 2.7 version): The same script as the above, but for the (soon to be obsolete) Python 2.7 version.
Requirements: Python 2.7
Cremer-Pople Carbohydrate Ring Puckering calculator (for PyMOL 2.1 or later with Python 3.x) support: A Python 3.x / PyMOL script that implements functions for performing Cremer-Pople (CP) puckering calculations for carbohydrate rings. The method is based on the approach presented by Hill and Reilly in Hill, A.D., Reilly, P.J. (2007) Puckering coordinates of monocyclic rings by triangular decomposition.J. Chem. Inf. Model. 47(3):1031-5, doi: 10.1021/ci600492e. This version of the script is for any PyMOL 2.x versions that are built upon Python 3 (both commercial and open-source versions). Users of PyMOL 1.5 and/or 2.0, built upon Python 2.7, should use the 2.7 version of the script, displayed below. Results from this script, used in measurements of the oligosaccharide core of Lipopolysaccharides (LPSs) have appeared in Baltoumas et al, J. Comput. Chem. Jul 5; 40(18): 1727-1734.
Requirements: Python 3.x, PyMOL 2.1 or later with Python 3 support.
Cremer-Pople Carbohydrate Ring Puckering calculator (for PyMOL 1.5-2.0 or later with Python 2.7) support: The same script, built for PyMOL versions that use Python 2.7. The script may work for the legacy De Lano versions (0.98-1.2), but it has not been tested enough for them.
Requirements: Python 2.7, PyMOL 1.5-2.0 with Python 2 support.
RTK-PRED: Downloadable version of the RTK-PRED pipeline for the automated detection and classification of Receptor-Tyrosine Kinases (RTKs).
Requirements: Python 3 version 3.5 or newer, HMMER version 3.1b or newer, and (optional) Phobius. Please read the README of the GitHub repository for detailed instructions.
Requirements: Unix-like OS environment (Linux, or Windows 10 with WSL enabled), R, R/shiny, a number of R libraries, LibreOffice, imagemagick, ghostscript, pdf2htmlEX and a number of other Linux packages for file conversion. R-studio (preferred) or, alternatively, shiny-server are required to deploy. Please read the README of the GitHub repository for detailed instructions.