There have been recent computational approaches that have been developed to invert the analytical spectrometric data to identify molecules. Although, de novo generation of structure from NMR spectra has been attempted with reasonable success , the inversion of tandem mass spectrometric (MS 2 ) data remains a challenge. Spec2Mol and MassGenie made some advances in this space, by training on electron-ionization mass spectrometry data and generating simpler small molecule metabolites , and MSNovelist worked on the problem using electrospray ionization mass spectrometry (ESI-MS) data . A key bottleneck in off-the-shelf usage of these existing methods lies in the lack of fine-tuning for specific drug-like molecules. These models have been trained on datasets, such as those obtained from MassBank and NIST spectral libraries , which cover a more general portion of the chemical space, rather than focusing on drug-like molecules.