A Record-Breaking Quantum Milestone
Scientists at Cleveland Clinic, RIKEN, and IBM have hit a historic milestone. Together, they simulated protein complexes containing up to 12,635 atoms. This is the largest-known molecular simulation ever performed using quantum hardware.
The result matters beyond its impressive scale. Quantum computers are no longer just experimental curiosities. Instead, they now deliver results that have direct relevance to science.
How Big Is This Achievement?
The team’s primary target was trypsin, a biologically important protein complex. Notably, this scale is about 40 times larger than what the same method could achieve just six months ago. Additionally, simulation accuracy improved by up to 210 times over that same period. That rate of progress is extraordinary.
Why Proteins Are Hard to Simulate
The Core Challenge in Life Sciences
Proteins are central to biological function. Understanding how a drug binds to a protein target ranks among the hardest problems in life sciences research. Traditional computers struggle to solve this problem exactly as molecules grow in size.
Furthermore, inaccurate simulations lead to costly errors in drug development. Currently, bringing a single medicine to market can take over a decade and require enormous investment. Early-stage improvements in computational accuracy could meaningfully change that timeline.
The Gap Quantum Computing Aims to Fill
Classical computers handle large-scale tasks well. However, they lack the precision needed to model quantum-mechanical behavior in molecules. Quantum computers, by contrast, are purpose-built for exactly this kind of calculation — and this research demonstrates that they are ready to contribute.
How Quantum-Centric Supercomputing Works
Pairing Quantum and Classical Power
IBM describes this collaborative framework as quantum-centric supercomputing. In short, quantum processors handle the parts of a problem that demand quantum precision. Classical computers, meanwhile, manage everything else.
In this study, classical systems first broke the protein-ligand complexes into computable fragments. Then, IBM’s 156-qubit Heron quantum processors calculated each fragment’s quantum-mechanical behavior. Finally, classical computers reassembled those results into a complete molecular model.
The Hardware Behind the Breakthrough
Two of the world’s most powerful supercomputers supported this effort. Fugaku, hosted at RIKEN in Japan, handled large-scale classical processing. Miyabi-G, run jointly by the University of Tokyo and the University of Tsukuba, also played a key role.
IBM quantum computers at both Cleveland Clinic (United States) and RIKEN (Japan) ran the quantum calculations simultaneously. Together, these systems used up to 94 qubits and executed nearly 6,000 quantum operations within a single simulation run.
The Algorithm That Made It Possible
Introducing EWF-TrimSQD
Hardware alone did not drive this leap in scale. A new quantum-classical hybrid algorithm called EWF-TrimSQD was equally critical. This novel method dramatically reduced computational overhead. As a result, researchers could directly model the chemistry of large molecular systems on quantum hardware for the first time.
A Clear Path Forward
Moreover, EWF-TrimSQD opens a defined roadmap for further scaling. Researchers expect to simulate even larger and more accurate molecular systems as both algorithms and quantum hardware continue to mature. The frontier of what is computationally possible has clearly shifted.
What This Means for Drug Discovery
Crossing the 12,000-Atom Barrier
“By crossing the 12,000-atom barrier, we have significantly expanded the scale of biologically meaningful molecular simulations possible with quantum computing,” said Kenneth Merz, Ph.D., lead author and Staff Scientist at Cleveland Clinic’s Computational Life Sciences Department. His team views this result as a starting point, not a conclusion.
Two Core Capabilities Now Within Reach
Accurate drug discovery simulation rests on two fundamental capabilities. First, it requires modeling how atoms move during biological processes. Second, it demands precise calculation of those atoms’ energies. Consequently, this research provides strong evidence that quantum-centric supercomputing can now support both capabilities at scale.
Beyond Pharmaceuticals
The implications reach further than drug development. Quantum simulation could eventually help researchers study enzyme catalysts, metabolic pathways, and molecular behaviors that today are only accessible through physical experimentation. Thus, the impact could span biology, chemistry, and materials science alike.
The Road Ahead for Quantum Science
A Shift in How Progress Is Measured
“For years, quantum computing has been a promise. Now, quantum computers are producing results that matter to science,” said Jay Gambetta, Director of IBM Research and IBM Fellow. That statement reflects a genuine turning point.
Historically, the quantum computing field measured progress through qubits, gate counts, and error rates. Today, however, progress can also be measured by the size and significance of the real-world problems that quantum systems can solve.
Building on a Series of Milestones
This breakthrough builds on prior achievements by the same three institutions. Earlier work appeared on the cover of Science Advances and introduced techniques to model electronic states in iron sulfide molecules. Furthermore, the team previously demonstrated the 303-atom Trp-cage benchmark — the first-known full quantum-centric simulation of a complete amino acid structure.
Each milestone accelerates the next. Together, Cleveland Clinic, RIKEN, and IBM are building a track record that positions quantum-centric supercomputing as an indispensable scientific tool for the decade ahead.
