Dr. Rino Ragno is a Full Professor at the Department of Chemistry and Pharmaceutical Technology , Sapienza University of Rome. His academic career spans decades of innovation in drug design , computational chemistry , and machine learning applications for chemical-biological systems. He teaches courses like Pharmaceutical and Toxicological Chemistry I and Computational Medicinal Chemistry , accessible via elearning.uniroma1.it. Research focuses on small molecule design , natural product analysis , and predictive modeling Developed the 3D-QSAR PORTAL for molecular modeling and drug discovery Active in essential oil characterization for antimicrobial, anticancer, and anti-inflammatory applications Recent publications emphasize machine learning classification models for essential oil activity prediction, anti-Bcl-2 cancer therapies , and AI-driven drug discovery . His lab employs multidisciplinary approaches combining experimental data with computational analysis to identify bioactive compounds and optimize drug candidates. The 3D-QSAR PORTAL, a free non-profit web platform, enables conformational analysis , molecular docking , and 3D-QSAR modeling accessible across electronic devices. Current projects include essential oil-based biocides for cultural heritage conservation and nanoemulsion formulations for drug delivery systems.
