Expanding Chemical Representation with k-mers and Fragment-based Fingerprints for Molecular Fingerprinting

arXiv:2403.19844v1 Announce Type: cross
Abstract: This study introduces a novel approach, combining substruct counting, $k$-mers, and Daylight-like fingerprints, to expand the representation of chemical structures in SMILES strings. The integrated method generates comprehensive molecular embeddings that enhance discriminative power and information content. Experimental evaluations demonstrate its superiority over traditional Morgan fingerprinting, MACCS, and Daylight fingerprint alone, improving chemoinformatics tasks such as drug classification. The proposed method offers a more informative representation of chemical structures, advancing molecular similarity analysis and facilitating …

abstract arxiv cs.lg embeddings expand experimental fingerprints information novel physics.chem-ph power q-bio.bm representation strings study type