Moltemplate
Description
Moltemplate
is a general cross-platform text-based molecule builder for
LAMMPS.
Moltemplate was intended for building custom coarse-grained molecular models,
but it can be used to prepare realistic all-atom simulations as well.
It currently supports the
ATB molecule database, the
OPLSAA(2023),
OPLSUA(2008),
LOPLS(2015),
AMBER(GAFF,GAFF2),
DREIDING,
COMPASS,
TraPPE(1998),
EFF,
force fields,
and the
MOLC,
mW,
ELBA(water),
and
oxDNA2,
molecular models (and others).
(New force fields and examples are added continually by users.)
Moltemplate is inter-operable with
ATB,
Open Babel,
AmberTools,
LigParGen,
RED-server,
VMD,
topotools,
PACKMOL,
EMC,
CellPACK,
Vipster,
struc2lammpsdf,
and any other program that generates MOL2 or LAMMPS DATA (.lmpdat) files (by using the mol22lt.py and ltemplify.py file converters).
This repository contains 3 folders:
Documentation
The best way to learn how to use moltemplate is to find an example
which is similar to the system that you wish to simulate and modify it.
This repository includes approximately 50 examples.
Some of the moltemplate examples are also demonstrated (with pictures)
here.
All moltemplate users should read chapter 4 of the
reference manual
(It’s only 6 pages long. The first 3 chapters can be skipped.)
Chapters 6, 7, and 5.1-5.3 also also recommended.
(13 pages.)
In addition, there are also several
talks/tutorials
online.
Strategies for preparing all-atom simulations
Moltemplate was originally designed for preparing coarse-grained simulations.
Fully atomistic simulations usually require choosing
force-field specific atom types (“atom typing”),
and the calculation of atomic charge.
Moltemplate
does not do this.
Moltemplate also does not repair incomplete PDB files.
To get around these limitations:
- Users can use use 3rd-party molecule-builder tools such as:
the ATB database (LT format),
AmberTools (MOL2 format),
LigParGen (DATA format),
OpenBabel, and
EMC (DATA format).
These tools can generate MOL2 or LAMMPS-DATA files
which can be converted into moltemplate format (LT format) using
mol22lt.py or
ltemplify.py.
(If you want to try and select the atom types
manually instead of using 3rd-party tools, read
these suggestions.)
Alternatively, users can use the
DREIDING force field
which has relatively simple
atom type rules.
- For atomic partial charges
the RED-server
is useful (which can generate a MOL2 file),
in addition to the tools listed above.
Alternatively, users can try using LAMMPS’ built-in
fix qeq feature.
Typical usage
moltemplate.sh [-atomstyle style] [-pdb/-xyz coord_file] [-vmd] system.lt
Installation Instructions
Moltemplate depends on other software to work
(such as BASH, python3, pip3, or conda). Once these
dependencies have been met, installing moltemplate is relatively easy.
However many users find it difficult to install these prerequisites correctly.
A detailed installation guide is located here.
Installation for conda users
If you have installed conda, you can download moltemplate using:
conda install conda-forge::moltemplate
This will omit the moltemplate examples
and documentation.
You can browse examples online
and/or download them using:
git clone https://github.com/jewettaij/moltemplate DESTINATION_DIRECTORY
Installation for pip users
You can download moltemplate using:
git clone https://github.com/jewettaij/moltemplate DESTINATION_DIRECTORY
(See below if you don’t have git installed.)
Then enter the directory where this README file is located:
cd DESTINATION_DIRECTORY
…and run the following command:
pip3 install . # (or "pip", if that fails)
(Note: In some environments, “pip3” is called “pip” instead.)
If the command above fails (with both “pip” and “pip3”), then try this instead:
pip3 install . --user # (or "pip", if that fails)
This will install moltemplate for a single user.
If you are on a shared computer and you want to install moltemplate
system-wide, then use:
sudo pip3 install . # (or "pip", if that fails)
Later, you can uninstall moltemplate using:
pip3 uninstall moltemplate
# (use "pip" and/or prepend "sudo" if you did that earlier)
If this fails then read the
installation troubleshooting guide.
This guide will offer several different installation methods
and explain how to install the prerequisites needed.
Note:
Alternatively, you can download and install moltemplate
using a single command:
pip3 install git+https://github.com/jewettaij/moltemplate.git # (or "pip", if that fails)
…however this will omit all of the examples and documentation.
Web page
Additional suggestions and supporting code can be found at:
http://www.moltemplate.org
Requirements
Moltemplate requires BASH and Python (3.4+), NumPy,
and can run on MacOS, linux, or windows.
(Note: On MacOS, it may eventually become necessary to use 3rd-party tools
like “brew” to install BASH if apple removes BASH support in future updates.
Python 2.7 may also work, but you must edit your
PATH
to install moltemplate instead of using pip/pip3.
Pip no longer works with old versions of python.)
To use LAMMPS and moltemplate, you will also need to install (and learn how to
use) a (unix-style) text editor. (Word, Wordpad, and Notepad will not work.)
Popular graphical text editors
include Atom, Sublime, Notepad++, and VSCode.
Older, non-graphical programs include vim, emacs,
nano, ne, and jove.
(Apple’s TextEdit can be used if you save the file as plain text.)
License
With the exception of one file
(ttree_lex.py),
moltemplate is available under the terms of the MIT license.
The remaining file, (ttree_lex.py),
is a modified version of the
shlex.py module,
which was released using the
PSF license.
Hence ttree_lex.py must also use this license.
(The PSF is not a copyleft license.
It is similar to the BSD and MIT licenses and
is compatible with the the GPL license.)
Citation
If you find this program useful, please cite:
“Moltemplate: A Tool for Coarse-Grained Modeling of Complex Biological Matter and Soft Condensed Matter Physics”, J. Mol. Biol., 2021, 433(11):166841, Jewett AI, Stelter D, Lambert J, Saladi SM, Roscioni OM, Ricci M, Autin L, Maritan M, Bashusqeh SM, Keyes T, Dame RT, Shea J-E, Jensen GJ, Goodsell DS
https://doi.org/10.1016/j.jmb.2021.166841
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