A novel scoring algorithm based on molecular interaction fingerprints (IFPs) was comparatively evaluated in its scaffold hopping efficiency against four virtual screening standards (GlideXP, Gold, ROCS, and a Bayesian classifier). Decoy databases for the two targets under examination, adenosine deaminase and retinoid X receptor alpha, were obtained from the Directory of Useful Decoys and were further enriched with approximately 5% of active ligands. Structure and ligand-based methods were used to generate the ligand poses, and a Tanimoto metric was chosen for the calculation of the similarity interaction fingerprint between the reference ligand and the screening database. Database enrichments were found to strongly depend on the pose generator algorithm. In spite of these dependencies, enrichments using molecular IFPs were comparable to those obtained with GlideXP, Gold, ROCS, and the Bayesian classifier. More interestingly, the molecular IFP scoring algorithm outperformed these methods at scaffold hopping enrichment, regardless of the pose generator algorithm.