Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More
Socket
Sign inDemoInstall
Socket

mordred

Package Overview
Dependencies
Maintainers
1
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

mordred

molecular descriptor calculator

  • 1.2.0
  • PyPI
  • Socket score

Maintainers
1

mordred

molecular descriptor calculator.

.. image:: https://travis-ci.org/mordred-descriptor/mordred.svg?branch=master :target: https://travis-ci.org/mordred-descriptor/mordred

.. image:: https://coveralls.io/repos/github/mordred-descriptor/mordred/badge.svg?branch=master :target: https://coveralls.io/github/mordred-descriptor/mordred?branch=master

.. image:: https://codeclimate.com/github/mordred-descriptor/mordred/badges/gpa.svg :target: https://codeclimate.com/github/mordred-descriptor/mordred :alt: Code Climate

.. image:: https://anaconda.org/mordred-descriptor/mordred/badges/version.svg :target: https://anaconda.org/mordred-descriptor/mordred

.. image:: https://img.shields.io/pypi/v/mordred.svg :target: https://pypi.python.org/pypi/mordred

.. image:: https://img.shields.io/badge/doi-10.1186%2Fs13321--018--0258--y-blue.svg :target: https://doi.org/10.1186/s13321-018-0258-y

.. image:: https://img.shields.io/badge/slack-mordred--descriptor-brightgreen.svg :target: https://join.slack.com/t/mordred-descriptor/shared_invite/enQtMzc1MzkyODk1NTY5LTdlYzM4MWUzY2YwZmEwMWYzN2M4YTVkMGRlMDY0ZjU2NjQ1M2RiYzllMzVjZGE4NGZkNWZjODBjODE0YmExNjk

number of descriptors

.. code:: python

>>> from mordred import Calculator, descriptors
>>> n_all = len(Calculator(descriptors, ignore_3D=False).descriptors)
>>> n_2D = len(Calculator(descriptors, ignore_3D=True).descriptors)
>>> print("2D:    {:5}\n3D:    {:5}\n------------\ntotal: {:5}".format(n_2D, n_all - n_2D, n_all))
2D:     1613
3D:      213
------------
total:  1826

Installation

conda(recommended)

#. install conda

       -  `miniconda <http://conda.pydata.org/miniconda.html>`__
       -  `anaconda <https://www.continuum.io/why-anaconda>`__

#. install mordred

       .. code:: console

           $ conda install -c rdkit -c mordred-descriptor mordred

pip
~~~

#. install `rdkit <http://www.rdkit.org/>`__ python package
#. install mordred

       .. code:: console

           $ pip install 'mordred[full]'  # install with extra requires
           # or
           $ pip install mordred
           
Testing the installation
------------------------

            $ python -m mordred.tests

examples
--------

as command
~~~~~~~~~~

calculate all descriptors

.. code:: console

    $ python -m mordred example.smi
    name,ECIndex,WPath,WPol,Zagreb1, (snip)
    benzene,36,27,3,24.0, (snip)
    chrolobenzene,45,42,5,30.0, (snip)


save to file (display progress bar)

.. code:: console

    $ python -m mordred example.smi -o example.csv
    50%|███████████████████████████████████████▌                                       | 1/2 [00:00<00:00,  7.66it/s]


stream read (low memory, no number of molecules information)

.. code:: console

    $ python -m mordred example.smi -s -o example.csv
    0it [00:00, ?it/s]

only ABCIndex

.. code:: console

    $ python -m mordred example.smi -d ABCIndex
    name,ABC,ABCGG
    benzene,4.242640687119286,3.9999999999999996
    chlorobenzene,5.059137268047012,4.785854275382693

ABCIndex and AcidBase

.. code:: console

    $ python -m mordred example.smi -d ABCIndex -d AcidBase
    name,ABC,ABCGG,nAcid,nBase
    benzene,4.242640687119286,3.9999999999999996,0,0
    chlorobenzene,5.059137268047012,4.785854275382693,0,0

multiple input

.. code:: console

    $ python -m mordred example.smi example2.smi -d ABCIndex
    name,ABC,ABCGG
    benzene,4.242640687119286,3.9999999999999996
    chlorobenzene,5.059137268047012,4.785854275382693
    pentane,2.8284271247461903,3.1462643699419726

show help

.. code:: console

    $ python -m mordred --help
    usage: python -m mordred [-h] [--version] [-t {auto,sdf,mol,smi}] [-o OUTPUT]
                             [-p PROCESSES] [-q] [-s] [-d DESC] [-3] [-v]
                             INPUT [INPUT ...]

    positional arguments:
      INPUT

    optional arguments:
      -h, --help            show this help message and exit
      --version             input molecular file
      -t {auto,sdf,mol,smi}, --type {auto,sdf,mol,smi}
                            input filetype (default: auto)
      -o OUTPUT, --output OUTPUT
                            output file path (default: stdout)
      -p PROCESSES, --processes PROCESSES
                            number of processes (default: number of logical
                            processors)
      -q, --quiet           hide progress bar
      -s, --stream          stream read
      -d DESC, --descriptor DESC
                            descriptors to calculate (default: all)
      -3, --3D              use 3D descriptors (require sdf or mol file)
      -v, --verbosity       verbosity

    descriptors: ABCIndex AcidBase AdjacencyMatrix Aromatic AtomCount
    Autocorrelation BalabanJ BaryszMatrix BCUT BertzCT BondCount CarbonTypes Chi
    Constitutional CPSA DetourMatrix DistanceMatrix EccentricConnectivityIndex
    EState ExtendedTopochemicalAtom FragmentComplexity Framework GeometricalIndex
    GravitationalIndex HydrogenBond InformationContent KappaShapeIndex Lipinski
    McGowanVolume MoeType MolecularDistanceEdge MolecularId MomentOfInertia MoRSE
    PathCount Polarizability RingCount RotatableBond SLogP TopologicalCharge
    TopologicalIndex TopoPSA VdwVolumeABC VertexAdjacencyInformation WalkCount
    Weight WienerIndex ZagrebIndex

as library
^^^^^^^^^^

.. code:: python

    >>> from rdkit import Chem
    >>> from mordred import Calculator, descriptors

    # create descriptor calculator with all descriptors
    >>> calc = Calculator(descriptors, ignore_3D=True)

    >>> len(calc.descriptors)
    1613

    >>> len(Calculator(descriptors, ignore_3D=True, version="1.0.0"))
    1612

    # calculate single molecule
    >>> mol = Chem.MolFromSmiles('c1ccccc1')
    >>> calc(mol)[:3]
    [4.242640687119286, 3.9999999999999996, 0]

    # calculate multiple molecule
    >>> mols = [Chem.MolFromSmiles(smi) for smi in ['c1ccccc1Cl', 'c1ccccc1O', 'c1ccccc1N']]

    # as pandas
    >>> df = calc.pandas(mols)
    >>> df['SLogP']
    0    2.3400
    1    1.3922
    2    1.2688
    Name: SLogP, dtype: float64

see `examples <https://github.com/mordred-descriptor/mordred/tree/develop/examples>`_

Citation
--------
Moriwaki H, Tian Y-S, Kawashita N, Takagi T (2018) Mordred: a molecular descriptor calculator. Journal of Cheminformatics 10:4 . doi: `10.1186/s13321-018-0258-y <https://doi.org/10.1186/s13321-018-0258-y>`__

Documentation
-------------

-  `master <http://mordred-descriptor.github.io/documentation/master>`__
-  `develop <http://mordred-descriptor.github.io/documentation/develop>`__

-  `v1.1.0 <http://mordred-descriptor.github.io/documentation/v1.1.1>`__
-  `v1.0.0 <http://mordred-descriptor.github.io/documentation/v1.0.0>`__

Keywords

FAQs


Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap
  • Changelog

Packages

npm

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc