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Welcome to SSTMap Release version 1.1.4 Thank you for using SSTMap, we've gone through a great deal of work trying to ensure compatibility with various operating systems and MD packages though we have not covered all the possible combinations. If you run into a bug, please report it on the issues and we will work to quickly resolve it.

Thank you,

Kamran and the Development Team.

SSTMap

SSTMap is a tool to study structural and thermodynamic properties of water molecules on solute surfaces. It combines grid inhomogeneous solvation theory (IST) with measures of water structure to produce mapping of solvation structure and thermodynamics in protein binding sites and on the surfaces of other molecules of interest, such as small-molecules or host-guest systems. It provides both site-based and grid-based calculations in one package, with support for multiple MD packages and can be integrated into Python’s scientific computing environment for advanced applications. The cross-platform support is enabled by trajectory and topology parsers of MDTraj and ParmEd.

Installation

Please check the instructions Here.

Usage

SSTMap provides command-line tools for hydration site analysis (HSA) and Grid Inhomogeneous Solvation Theory (GIST), run_hsa and run_gist, respectively. The functionality of SSTMap is also available through its Python API, available as the sstmap module. For more details, please visit sstmap.org.

An example of running a quick HSA and GIST calculation on a test system available in sstmap_test_suite. You can download the full test suite from here (since Github repository doesn't contain trajectory files). For a given platform, cd to its sub-directory and run the commands as shown below.

cd sstmap_test_suite/platforms/amber
$ run_hsa -i testcase.prmtop -t md100ps.nc -l ligand.pdb -s 0 -f 100 -o testcase
$ run_gist -i testcase.prmtop -t md100ps.nc -l ligand.pdb -g 20 20 20 -s 0 -f 100 -o testcase

For examples using MD simulations generated from other packages, such as Amber, Charmm, Gromacs, NAMD, OpenMM and Desmond, please follow this tutorial on sstmap.org. SSTMap can also be used as a Python module:

import sstmap as sm
# Example 1: Run a grid-based calculation
# with all quantities.
gist = sm.GridWaterAnalysis(
        "casp3.prmtop", 
        "casp3.netcdf",
        ligand_file="casp3_ligand.pdb", 
        grid_dimensions=[40, 40, 40], 
        prefix="casp3")
gist.calculate_grid_quantities()
# Example 2: Run gist with only energy calculations.
gist.calculate_grid_quantities(energy=True)
# Example 3: Initialize gist with a grid center position.
gist = sm.GridWaterAnalysis(
        "casp3.prmtop", 
        "casp3.netcdf",
        grid_center=[35.33, 52.23, 54.96], 
        grid_dimensions=[40, 40, 40], 
        prefix="casp3")

Principal Developer(s)

Co-Developers

Principal Investigators

  • Tom Kurtzman
  • Michael Gilson

References

Please cite the following when you use this software.

[1] Haider K, Cruz A, Ramsey S, Gilson M. and Kurtzman T. Solvation Structure and Thermodynamic Mapping (SSTMap): An Open-Source, Flexible Package for the Analysis of Water in Molecular Dynamics Trajectories. J. Chem. Theory Comput. (10.1021/acs.jctc.7b00592) 2017. [2] Crystal N. Nguyen, Michael K. Gilson, Tom Young. Structure and Thermodynamics of Molecular Hydration via Grid Inhomogeneous Solvation Theory. eprint arXiv:1108.4876, (2011).

[3] Crystal N. Nguyen, Tom Kurtzman Young, and Michael K. Gilson. Grid inhomogeneous solvation theory: hydration structure and thermodynamics of the miniature receptor cucurbit[7]uril. J. Chem. Phys. 137, 044101 (2012)

[4] Haider K, Wickstrom L, Ramsey S, Gilson MK and Kurtzman T. Enthalpic Breakdown of Water Structure on Protein Active Site Surfaces. J Phys Chem B. 120:8743-8756, (2016). http://dx.doi.org/10.1021/acs.jpcb.6b01094.

[5] Themis Lazaridis. Inhomogeneous Fluid Approach to Solvation Thermodynamics. 1. Theory. The Journal of Physical Chemistry B 102 (18), 3531-3541, (1998). DOI: 10.1021/jp9723574

License

SSTMap is free software and is licensed under the MIT license.

Acknowledgements

This project is funded through the NIH Grant: R01-GM100946

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