Garnet Chan and a team of researchers from the California Institute of Technology have successfully modeled the nitrogenase enzyme using classical computing methods. This breakthrough, achieved in early January 2026, challenges the long-standing assumption that only quantum computers could solve such complex biochemical problems.
The study focused on the FeMo-co cluster, the active site of nitrogenase, which contains seven iron atoms and exhibits complex electron correlation. Researchers calculated the ground-state energy of this system, which involves over 78,000 possible electron configurations, by refining classical algorithms to identify and discard non-essential configurations.
For years, nitrogenase has served as a benchmark for quantum computing, with companies like Microsoft identifying it as a prime candidate for demonstrating quantum advantage. Proponents of quantum computing argue that while classical methods can solve specific systems after decades of work, they may lack the scalability required for broader applications.
Chan, who has studied nitrogenase for over two decades, argues that classical methods are evolving rapidly and remain a viable tool for chemical research. He maintains that while quantum computers may eventually play a significant role, scientific progress in understanding complex biological processes should not be delayed waiting for fault-tolerant quantum hardware.
