Greg Landrum b5595611a6 Fixes Issue 1614 (#1781)
* This makes assignStereochemistry cleanIt=True not remove CIS/TRANS
bond stereo chemistry that was manually added as described in issue #1614.

Incorrect CIS/TRANS stereochemistry will still be removed by
'cleanIt=true' if symmetry is detected. However, this symmetry
detection doesn't work in more complex pseudo-stereo chemistry cases:
bond stereo that depends on other bond stereo to break symmetry; and
bond stereo that depends on other atom stereo centers to break
symmetry. Test cases for these cases have been added ifdef'd in based
on USE_NEW_STEREOCHEMISTRY.

However, getting USE_NEW_STEREOCHEMISTRY to work in a copacetic way is
not trivial, I tried a little bit here to no avail. I'm leaving the
test cases checked in as they should be useful when we decide to make
the plunge into using Canon::chiralRankMolAtoms for symmetry detection
instead of the CIP ranks.

So this fixes at least the glaring issue of STEREOCIS and STEREOTRANS
being incorrectly removed by 'cleanIt=true' when it is indeed valid
stereo. The checks made for symmetry are rudimentary, but don't feel
complete.

* add another test; make what's being tested explicit

* test smiles generation and function when Hs have been added

* add a test that fails

* I think that it's ok to remove this

* backup

* At this point all tests pass.
Bond wedging is now handled even if sanitization is turned off when mol files are read

* adjust to code changes

* fix a couple problems caused by rebase

* update docs
2018-04-01 17:26:09 +02:00
2018-04-01 17:26:09 +02:00
2018-01-05 16:13:00 +00:00
2016-09-23 04:58:46 +02:00
2018-02-14 19:53:26 -05:00
2018-02-15 20:25:42 -05:00
2016-09-23 04:58:46 +02:00
2017-09-25 08:57:14 +02:00
2016-06-24 17:46:30 +02:00
2015-11-26 02:34:33 +01:00
2015-11-26 02:34:33 +01:00
2017-10-07 07:16:16 +02:00
2016-09-23 04:58:46 +02:00

RDKit

Build status Documentation Status DOI

RDKit is a collection of cheminformatics and machine-learning software written in C++ and Python.

  • BSD license - a business friendly license for open source
  • Core data structures and algorithms in C++
  • Python (2.x and 3.x) wrapper generated using Boost.Python
  • Java and C# wrappers generated with SWIG
  • 2D and 3D molecular operations
  • Descriptor and Fingerprint generation for machine learning
  • Molecular database cartridge for PostgreSQL supporting substructure and similarity searches as well as many descriptor calculators
  • Cheminformatics nodes for KNIME
  • Contrib folder with useful community-contributed software harnessing the power of the RDKit

Web presence

Code

Community

Materials from user group meetings

Documentation

Available on the RDKit page and in the Docs folder on GitHub

Installation

Installation instructions are available in Docs/Book/Install.md.

Binary distributions, anaconda, homebrew

  • Windows binaries are available with each release.
  • RPMs for RedHat Enterprise Linux, Centos, and Fedora. Contributed by Gianluca Sforna.
  • homebrew formula for building on the Mac. Contributed by Eddie Cao.
  • recipes for building using the excellent conda package manager. Contributed by Riccardo Vianello.

Projects using RDKit

  • ChEMBL Beaker - standalone web server wrapper for RDKit and OSRA
  • myChEMBL (blog post, paper) - A virtual machine implementation of open data and cheminformatics tools
  • sdf_viewer.py - an interactive SDF viewer
  • sdf2ppt - Reads an SDFile and displays molecules as image grid in powerpoint/openoffice presentation.
  • MolGears - A cheminformatics tool for bioactive molecules
  • PYPL - Simple cartridge that lets you call Python scripts from Oracle PL/SQL.
  • shape-it-rdkit - Gaussian molecular overlap code shape-it (from silicos it) ported to RDKit backend
  • WONKA - Tool for analysis and interrogation of protein-ligand crystal structures
  • OOMMPPAA - Tool for directed synthesis and data analysis based on protein-ligand crystal structures
  • DeepChem - Machine learning library for small molecules

License

Code released under the BSD license.

Description
No description provided
Readme 380 MiB
Languages
C++ 69.6%
Python 15.3%
PLSQL 3.6%
CMake 2.8%
C 2.5%
Other 6.1%