Release 4.7

• SynthSense: enhanced version of CAZP
• Integration of Syngenta's PUMAS scoring subsystem
• iSIM support for TL
• Variants of penalty functions and RND-based filter
• Inception for all generators
• Multi-score support in maize scoring component
• Improvements to ring precedence scoring component
• Fix in CamSol scoring component
• Intel XPU support
• Safer SMILES checks
• Removed JSON configuration examples and add conversion script

Release 4.6

• All priors now on Zenodo
• CAZP scoring component: interface to AiZynthFinder
• Optional SMARTS filter for sampling to remove unwanted patterns e.g. elements
• Output SMILES state for sampling
• iSIM similarty support for RL in TensorBoard
• Parallel scoring
• Ring system precedence based scoring component (from Pat Walters)
• Multiple endpoints for ExternalProcess scoring component
• ChemProp is still 1.x: rdkit_2d_normalized is obsolete (but needed and ignored) use features="rdkit_2d_normalized"
• Write out metadata to CSV e.g. custom alert matching pattern
• GPU memory reporting for TL
• Terminate if invalid tokens are found in the input
• Additions and fixes to PepInvent e.g CamSol scoring component
• Updates to the data pipeline e.g. optional InchiKey deduplication
• Various code improvements and fixes

Release 4.5

New in REINVENT 4.5

For details see CHANGELOG.md.

• PepINVENT: transformer (SMILES) based peptide generator and prior model
• Temperature factor parameter (transformer generators) for sampling and RL
• Support script run-qsartuna.py to play QSARtuna models in external environment
• Component-level parameters for scoring components
• Renamed Qptuna scoring component to QSARtuna
• Staged learning terminates on SIGTERM (Ctrl-C) and writes out checkpoint file
• SIGUSR1 for graceful termination of staged learning runs
• Relaxed dependencies to accomodate install of other software in same environment e.g. QSARtuna
• Updated some dependencies e.g. PyTorch (now at version 2.4.1)
• New notebook in contrib demoing docking with DockStream and OpenEye
• YAML configuration file reader
• Configuration file format is automatically detected from filename extension
• Various code improvements and fixes

Release 4.4

New in REINVENT 4.4

For details see CHANGELOG.md.

• Transformer based Libinvent
• Prior registry to load internal priors more easily
• Strict validation of input configuration to ensure consistency
• Better JSON configuration file writing
• Metadata writing for all created RL and TL models
• Import functionality for scoring runmode
• Stages in staged learning can have their own diversity filters
• More memory efficient transformer models to handle larger numbers of input SMILES
• Additional (fragment) SMILES written to staged learning CSV
• TanimotoDistance renamed to TanimotoSimilarity
• Support for ChemProp multitask models: requires param.target_column
• Allow dot SMILES fragment separator for Lib/Linkinvent input
• Optional [scheduler] section for TL
• Example support script for RAScore
• A more complete RL/TL demo notebook
• Experimental data pipeline to preprocess SMILES for prior creation
• Various code improvements and fixes

Release 4.3

New in REINVENT 4.3

For details see CHANGELOG.md.

• Upgrade to PyTorch 2.2: rerun pip install -r requirements-linux-64.lock
• 2 new notebooks demoing Reinvent with reinforcement learning and also transfer learning, includes TensorBoard visualisation and basic analysis
• New Linkinvent model code based on unified transformer
• New PubChem Mol2Mol prior
• Unknown token support for PubChem based transformer models
• New "device" config parameter to allow for explicit device e.g. "cuda:0"
• Optional SMILES randomization in every TL epoch for Reinvent
• Dataclass parameter validation for most scoring components
• Invalid SMILES are now written to the reinforcement learning CSV
• Code improvements and fixes

Release 4.2

New in REINVENT 4.2
For details see CHANGELOG.md.

Reworked TL code with added options and statistics
Standardization can be switched off in TL (useful in new prior creation)
Similarity calculation in TL made optional
Updated script for empty classical Reinvent model creation
Allow runs with only filter/penalty components
Stable sigmoid functions
Removed long chain check in SMILES processing
Unified transformer code
Filter apply to transformed scores
Better memory handling in inception
Better logging for Reinvent standardizer
Inception filters for tokens not compatible with the prior
Number of CPUs for TL (Mol2Mol pair generation) is 1 by default
Tensorboard histogram bug fixed again
Code improvements and fixes

Release 4.1

New in REINVENT 4.1

For details, see CHANGELOG.md.

• Scoring component MolVolume
• Scoring component for all 210 RDKit descriptors
• CSV and SMILES file reader for the scoring run mode
• Tobias Ploetz' (Merck) REINFORCE implementations of the DAP, MAULI and MASCOF RL reward strategies
• Number of CPUs can be specified for TL jobs: useful for Windows
• All prior models tagged with metadata and checked for integrity
• Code improvements and fixes

First Release 4.0

This is the first public release of the REINVENT4 series.