New RDKit Nightly Build with RDKit Binaries version 'KnimeNodes_Dec2014_Binary' and New Features

Dear All,

I uploaded a new version of our RDKit Nodes, version 2.5, to the nightly build with the following changes:

  • New RDKit Binaries 'KnimeNodes_Dec2014_Binary' . Details about this release can be found in GitHub: https://github.com/rdkit/rdkit/releases/tag/KnimeNodes_Dec2014_Binary
  • The new binaries bring the following changes that may change results of existing nodes:
    • RDKit Fingerprint Node: Avalon Fingerprint, Rooted Fingerprints for AtomPairs and Torsion
    • RDKit Optimize Geometry Node: Due to force field calculation changes
  • New Nodes:
    • RDKit MCS Node: This node is used to find the Maximum Common Substructure (MCS) of a set of compounds using the RDKit MCS code.
    • RDKit Structure Normalizer Node: Checks structures and tries to normalize them, if necessary. Structures that are normalized already will appear in the first output table. Structures, which need to be normalized will be corrected and also put in the first output table. Information about the normalization is made available as bit mask (flags) as well as warning messages. This node uses StruChk, an open source Avalon tool that comes as part of the RDKit in KNIME.
  • New Functionality:
    • MCS aggregation function available in KNIME's GroupBy Node
    • Python integration for the new KNIME Python Scripting Nodes - it is possible to transfer RDKit molecules between KNIME and Python, if the RDKit is also installed on Python (Note: This change is included already in the 2.11 version, but was not announced so far)
    • Added startup message that shows up if the LOCALE setting is not correct when using RDKit

Please test it... And as always: We appreciate your feedback and ideas!

Thanks for using RDKit :-)  -- Merry Christmas!

Kind regards,
Manuel Schwarze

The implementation of the MCS node is extremely cool with the number of options available and the versatile output as SMARTS. Nice job! This will be really useful.

Simon.

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