2014_09_1 (Q3 2014) Beta Release
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greglandrum
released this
20 Oct 04:08
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4708 commits
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****** Release_2014.09.1 *******
(Changes relative to Release_2014.03.1)
Acknowledgements:
Andrew Dalke, Jan Domanski, Patrick Fuller, Noel O'Boyle, Sereina
Riniker, Alexander Savelyev, Roger Sayle, Nadine Schneider, Matt
Swain, Paolo Tosco, Riccardo Vianello
Bug Fixes:
- Bond query information not written to CTAB
(github issue 266) - Bond topology queries not written to CTABs
(github issue 268) - Combined bond query + topology query not correctly parsed from CTAB
(github issue 269) - SWIG wrapped suppliers leak memory on .next()
(github issue 270) - SWIG wrappers don't build with SWIG 3.0.x
(github issue 277) - core leak from DataStructs.ConvertToNumpyArray
(github issue 281) - MolTransforms not exposed to Java wrapper
(github issue 285) - Seg fault in ReactionFromRxnBlock
(github issue 290) - BitInfo from GetHashedMorganFingerprint() has non-folded values
(github issue 295) - bad inchi for chiral S when the molecule is sanitized
(github issue 296) - Cannot generate smiles for ChEBI 50252
(github issue 298) - Either molecule-molecule substruct matching is wrong OR the docs for Atom::Match incorrect
(github issue 304) - fluorine F-F gives segmentation fault with MMFF forcefield
(github issue 308) - cartridge: MACCS similarity wrong when using the builtin popcount and the index
(github issue 311) - Substructure Search via SMARTS implicit hydrogens
(github issue 313) - SMARTS output for [x] is wrong
(github issue 314) - Bonds not being set up properly in renumberAtoms
(github issue 317) - Python 2 code in python 3 branch
(github issue 326) - Linking error with ICC 15.0 on Linux
(github issue 327) - Using explicit hydrogens in the SMILES lead to the same AP FP for two different molecules
(github issue 334) - memory leaks when smiles/smarts parsers fail
(github issue 335) - No double bond stereo perception from CTABs when sanitization is turned off
(github issue 337) - missing MACCS key 44 might be found
(github issue 352) - Fixed a weakness in the angular restraint code
(github pull 261 from ptosco) - A few fixes to improve MMFF/UFF robustness
(github pull 274 from ptosco) - Static webGL rendering fix
(github pull 287 from patrickfuller) - Revert #include ordering in SmilesMolSupplier.cpp
(github pull 297 from mcs07) - Add missing include for RDDepict::compute2DCoords
(github pull 301 from baoilleach) - Herschbach-Laurie fallback implemented to fix GitHub 308
(github pull 312 from ptosco) - Issue #320 Making GetBestRMS more idiot-proof
(github pull 322 from jandom)
New Features:
- Should be able to do intramolecular bond breaking in reactions.
(github issue 58) - Support reactions in cartridge
(github issue 223) - Documentation of Inchi methods
(github issue 240) - add DescribeQuery() to Bond python wrapper
(github issue 267) - support avalon fingerprint in cartridge
(github issue 286) - support partial fragmentation with fragmentOnSomeBonds
(github issue 288) - Add calcNumHeterocycles() descriptor
(github issue 351) - C++ implementation of FMCS algorithm
- Reordering feature for Butina clustering
(github pull 302 from sriniker) - Changes and new functions for the calculation of RMS values between conformers of a molecule
(github pull 306 from sriniker) - Extended chemical reaction functionality and add chemical reactions to cartridge
(github pull 315 from NadineSchneider) - Custom color to highlight atoms in Mol2Image
(github pull 316 from jandom) - Several different fingerprint algorithms for chemical reactions are now available
New Database Cartridge Features:
- Chemical reactions and several operations on them are now supported
- Avalon fingerprints now supported (when support has been compiled in)
New Java Wrapper Features:
- FMCS implementation exposed
- Fingerprints for chemical reactions
- Possible core leak in some of the MolSuppliers was fixed
Deprecated modules (to be removed in next release):
Removed modules:
Contrib updates:
Other:
- The RDKit now supports both python3 and python2.
- There is now conda integration for the RDKit.
- SMILES generation is substantially faster