Anton “Tony” Hopfinger

It is with great sadness that the MGMS announces the passing of Prof. Anton “Tony” Hopfinger. He was a pioneer in the field of molecular modeling and cheminformatics, particularly known for Quantitative Structure-Activity Relationships (QSAR) and Quantitative Structure-Property Relationships (QSPR).

Tony graduated from the University of Wisconsin Oshkosh with bachelor’s degrees in mathematics and physics, and later a doctorate in biophysical chemistry from Case Western Reserve University.

He served as a Distinguished Research Professor of Pharmacy at the University of New Mexico, Professor Emeritus of Medicinal Chemistry and Pharmacognosy at the University of Illinois, and was the Founder, Chief Technical Officer and Secretary of The Chem21 Group.

Tony was also the recipient of the 2010 Herman Skolnik Award, granted by the ACS Division of Chemical Information — recognizing outstanding contributions to and achievements in the theory and practice of chemical information science and related disciplines.

He dedicated his life to teaching and research, developing software and databases for the design of new compounds, including novel drugs.

Tony’s work transformed computational chemistry and he became widely-known as pioneer of multidimensional quantitative structure-activity relationship, notably 4D-QSAR. He published more than 315 peer-reviewed papers, four books, and presented at nearly four-hundred invited lectures worldwide. He trained more than 50 doctoral students, and more than 70 postdoctoral associates.

Hopfinger’s impact extended well beyond academia. Emilio Xavier Esposito, Chief Science Officer of exeResearch LLC, said Tony helped to develop “Aspartame, one of the world’s leading artificial sweeteners; and Aricept, the blockbuster drug for treating early stage Alzheimer’s disease.” His work also gave birth to Celebrex, used to treat pain and inflammatory diseases.

Wendy Warr interviewed Tony in 2007, and asked him if he had any advice for young modellers; he said:

“I would tell them to take the time to learn enough physical and theoretical chemistry, enough statistics and enough pharmacology so as to be able to understand and critically question the applicability and reliability of the methods being employed in the software they are using or developing. Obviously this is not generally considered fun to do, but I really think modelers today have gotten too far away from a healthy skeptical and questioning attitude toward computational tools. My anchor point is to remember that we still cannot routinely calculate a reliable IC50 value which is the cornerstone measurement in preclinical drug discovery.”