e MolFrag 2 and e Synth 2: Sound Fragment-Based Molecular Decomposition and Reconstruction

Abstract

Abstract We present eMolFrag2 and eSynth2, enhanced successors to eMolFrag and eSynth for fragment-based molecular decomposition and reconstruction. eMolFrag2 is a complete reimplementation of eMolFrag in Python, using RDKit and graph-based molecular representations to preserve connectivity, identify free atoms, combine adjacent linkers, and avoid aromaticity ambiguities that impair downstream reconstruction. eSynth2 generalizes fragment recombination by removing hard-coded molecular-property filters, supporting multiple bonds to a single brick atom, and adding a targeted reconstruction mode for soundness validation. Across 36,534 nonredundant DUD-E active compounds, the eMolFrag2 → eSynth2 workflow reconstructed every input molecule exactly (Tanimoto coefficient, TC = 1.0), whereas the original eMolFrag→ eSynth workflow reconstructed 51 of the 100 molecules in a benchmark subset. The upgraded workflow also produced broader recombinant chemical spaces, including higher entropy in a four-molecule diversity analysis (2.78 versus 2.70). Both tools are open-source, platform-agnostic, and available for academic and commercial use.