Other Resources

In this page you will find additional resources for various Bioinformatics/Computational Biology and Structural Biophysics applications, including several analysis scripts (written in Perl, Python, Tcl/Tk or BASH), Force Field topology and parameters for various molecules, R & R/Shiny applications etc.

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.

 Note: all of the links offered below will take you to GitHub repositories.  Most of them are my own, some belong to other people, with whom I’ve collaborated on the respective projects.  If, for some reason, any of the links do not work, please let me know with an e-mail.


Molecular Dynamics



GROMACS v. 2018.1 compiled for Windows (Cygwin): GROMACS v. 2018.1, compiled for 64-bit Windows though Cygwin. GROningen MAchine for Chemical Simulations (GROMACS) is a molecular dynamics package mainly designed for simulations of proteins, lipids, and nucleic acids. It was originally developed in the Biophysical Chemistry department of University of Groningen, and is now maintained by contributors in universities and research centers worldwide. Notes on this particular GROMACS implementation: Single-precision build, No MPI or GPU capabilities, Fast-Fourier Transformation (FFT) library: FFTW.
Requirements: Cygwin 64-bit.



Force Field Parameters

MARTINI Cholesterol in NAMD format: NAMD-formatted topology and parameter files for Coarse-Grained cholesterol, based on the original MARTINI model (Marrink et al, J. Phys. Chem. B 2007, 111 (27),  7812-7824).
MARTINI parameters for phosphatidyl-inositols (POPI, DPPI, DOPI) in NAMD format: NAMD-formatted files for three PI lipids, intended for use with the MARTINI and PACE force fields.  Based on the equivalent GROMACS parameters, as presented in Lopez et al, JCTC, 9:1694–1708, 2013.
Divalent metal ion parameters:  Parameters for divalent metal ions (Fe2+, Mn2+, Mg2+, Be2+ etc) in GROMACS format for use with the TIP3P (CHARMM, AMBER) and SPC / SPCE (GROMOS) water models.  Based on the work by Li et al, J Chem Theory Comput 2013, 9(6):2733–2748.  The TIP3P compatible parameters have been previously used in Triantaphyllopoulos et al, J. Comput Aid. Mol. Des. 2019, 33:265–285 to model SLC11A1 – metal interactions.


Analysis Scripts

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.



Sequence Analysis


HMMER for Windows: HMMER version 3.2b compiled for 64-bit Windows. HMMER is a package for the creation and manipulation of profile Hidden Markov Models (pHMMs) for biological data (protein and nucleic acid sequences).
Requirements: Windows Command Line (CMD), PowerShell or Cygwin.


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.



Text Mining

OnTheFly2.0: Downloadable version of the OnTheFly 2.0 text annotation web service. OnTheFly2.0 is a tool that automates data collection and knowledge extraction from biological literature in a user friendly and efficient way. OnTheFly2.0 is able to extract bioentities from individual articles such as HTML, plain text, Microsoft Word, Excel and PDF files. Through an intuitive and easy-to-use graphical interface, the text of a document is extensively parsed for bioentities such as protein and gene names, chemical compounds, organisms, environmental entities and ontology terms. Utilizing high quality data integration platforms, OnTheFly2.0 allows the generation of informative summaries, interaction networks and at-a-glance popup windows containing knowledge related to the bioentities found in documents.
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.