Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/lukasturcani/stk
A Python library which allows construction and manipulation of complex molecules, as well as automatic molecular design and the creation of molecular databases.
https://github.com/lukasturcani/stk
cheminformatics chemistry computational-chemistry computational-science materials-design materials-discoveries materials-science materials-screening molecular-evolution molecular-modeling molecular-structures reactions
Last synced: 11 days ago
JSON representation
A Python library which allows construction and manipulation of complex molecules, as well as automatic molecular design and the creation of molecular databases.
- Host: GitHub
- URL: https://github.com/lukasturcani/stk
- Owner: lukasturcani
- License: mit
- Created: 2018-03-18T20:57:46.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-03-28T15:56:50.000Z (8 months ago)
- Last Synced: 2024-05-02T21:30:19.513Z (6 months ago)
- Topics: cheminformatics, chemistry, computational-chemistry, computational-science, materials-design, materials-discoveries, materials-science, materials-screening, molecular-evolution, molecular-modeling, molecular-structures, reactions
- Language: Python
- Homepage:
- Size: 44.8 MB
- Stars: 237
- Watchers: 11
- Forks: 43
- Open Issues: 63
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
Awesome Lists containing this project
README
:maintainers:
`lukasturcani `_,
`andrewtarzia `_
:documentation: https://stk.readthedocs.io
:discord: https://discord.gg/zbCUzuxe2B.. figure:: docs/source/_static/stk.png
.. image:: https://github.com/lukasturcani/stk/actions/workflows/tests.yml/badge.svg?branch=master
:target: https://github.com/lukasturcani/stk/actions?query=branch%3Amaster.. image:: https://readthedocs.org/projects/stk/badge/?version=latest
:target: https://stk.readthedocs.ioOverview
========``stk`` is a Python library which allows construction and
manipulation of complex molecules, as well as automatic
molecular design, and the creation of molecular, and molecular
property, databases. The documentation of ``stk`` is available on
https://stk.readthedocs.io and the project's Discord server can be
joined through https://discord.gg/zbCUzuxe2B.Installation
============To get ``stk``, you can install it with pip:
.. code-block:: bash
pip install stk
If you would like to get updated when a new release of ``stk`` comes
out, which happens pretty regularly, click on the ``watch`` button on
the top right corner of the GitHub page. Then select ``Releases only``
from the dropdown menu.You can see the latest releases here:
https://github.com/lukasturcani/stk/releases
There will be a corresponding release on ``pip`` for each release
on GitHub, and you can update your ``stk`` with:.. code-block:: bash
pip install stk --upgrade
Developer Setup
---------------1. Install `just`_.
2. In a new virtual environment run:.. code-block:: bash
just dev
3. Setup the `MongoDB`_ container (make sure ``docker`` is installed):
.. code-block:: bash
just mongo
4. Run code checks:
.. code-block:: bash
just check
.. _`just`: https://github.com/casey/just
.. _`MongoDB`: https://www.mongodb.com/docs/manual/tutorial/install-mongodb-on-ubuntu/How To Cite
===========If you use ``stk`` please cite
https://github.com/lukasturcani/stk
and
https://aip.scitation.org/doi/10.1063/5.0049708
Publications
============about stk
---------* `stk: An Extendable Python Framework for Automated Molecular and
Supramolecular Structure Assembly and Discovery`____ https://aip.scitation.org/doi/10.1063/5.0049708
* Describing metal-organic cage usage: `Unlocking the computational design of metal–organic cages`__
__ https://pubs.rsc.org/en/content/articlelanding/2022/CC/D2CC00532H
* (Out of date) `stk: A Python Toolkit for Supramolecular Assembly`__
| chemrxiv____ https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.25377
__ https://chemrxiv.org/articles/STK_A_Python_Toolkit_for_Supramolecular_Assembly/6127826using stk
---------* Using stk for constructing larger numbers of coarse-grained models: `Systematic exploration of accessible topologies of cage molecules via minimalistic models`__
__ https://pubs.rsc.org/en/content/articlelanding/2023/sc/d3sc03991a
* `The effect of disorder in multi-component covalent organic frameworks`__
__ https://pubs.rsc.org/en/content/articlehtml/2023/cc/d3cc01111a
* `Tetramine Aspect Ratio and Flexibility Determine Framework Symmetry for Zn8L6 Self-Assembled Structures`__
__ https://onlinelibrary.wiley.com/doi/10.1002/anie.202217987
* `Orientational self-sorting in cuboctahedral Pd cages`__
__ https://pubs.rsc.org/en/content/articlehtml/2022/sc/d2sc03856k
* `Conformer-RL: A deep reinforcement learning library for conformer
generation`____ https://onlinelibrary.wiley.com/doi/full/10.1002/jcc.26984
* `High-throughput Computational Evaluation of Low Symmetry Pd2L4
Cages to Aid in System Design`____ https://onlinelibrary.wiley.com/doi/10.1002/anie.202106721
* `Forecasting System of Computational Time of DFT/TDDFT Calculations
under the Multiverse Ansatz via Machine Learning and
Cheminformatics`____ https://pubs.acs.org/doi/full/10.1021/acsomega.0c04981
* `Using High-throughput Virtual Screening to Explore the
Optoelectronic Property Space of Organic Dyes; Finding
Diketopyrrolopyrrole Dyes for Dye-sensitized Water Splitting and
Solar Cells`____ https://pubs.rsc.org/en/content/articlelanding/2021/SE/D0SE00985G#!divAbstract
* `Accelerated Discovery of Organic Polymer Photocatalysts for Hydrogen
Evolution from Water through the Integration of Experiment and
Theory`____ https://pubs.acs.org/doi/abs/10.1021/jacs.9b03591
* `Structurally Diverse Covalent Triazine-Based Framework Materials for
Photocatalytic Hydrogen Evolution from Water`____ https://pubs.acs.org/doi/full/10.1021/acs.chemmater.9b02825
* `Mapping Binary Copolymer Property Space with Neural Networks`__
__ https://pubs.rsc.org/ko/content/articlehtml/2019/sc/c8sc05710a
* `An Evolutionary Algorithm for the Discovery of Porous Organic
Cages`__ | chemrxiv____ https://pubs.rsc.org/en/content/articlelanding/2018/sc/c8sc03560a#!divAbstract
__ https://chemrxiv.org/articles/An_Evolutionary_Algorithm_for_the_Discovery_of_Porous_Organic_Cages/6954557* `Machine Learning for Organic Cage Property Prediction`__
| chemrxiv____ https://pubs.acs.org/doi/10.1021/acs.chemmater.8b03572
__ https://chemrxiv.org/articles/Machine_Learning_for_Organic_Cage_Property_Prediction/6995018* `A High-Throughput Screening Approach for the Optoelectronic
Properties of Conjugated Polymers`__ | chemrxiv____ https://pubs.acs.org/doi/abs/10.1021/acs.jcim.8b00256
__ https://chemrxiv.org/articles/A_High-Throughput_Screening_Approach_for_the_Optoelectronic_Properties_of_Conjugated_Polymers/6181841* `Computationally-Inspired Discovery of an Unsymmetrical Porous
Organic Cage`__ | chemrxiv____ https://pubs.rsc.org/en/content/articlelanding/2018/nr/c8nr06868b#!divAbstract
__ https://chemrxiv.org/articles/Computationally-Inspired_Discovery_of_an_Unsymmetrical_Porous_Organic_Cage/6863684* `Maximising the Hydrogen Evolution Activity in Organic Photocatalysts
by co-Polymerisation`____ https://pubs.rsc.org/en/Content/ArticleLanding/TA/2018/C8TA04186E#!divAbstract
Acknowledgements
================I began developing this code when I was working in the Jelfs group,
http://www.jelfs-group.org/, whose members often provide me with
very valuable feedback, which I gratefully acknowledge.