Quantum computers provide a novel and paradigm-changing approach to accelerating the development of new drugs and medical treatments. A key potential of quantum computers is to address the bottleneck in today’s drug development: the inability of conventional computers to accurately predict quantum chemical dynamics in molecules.
Here, I will summarize our interdisciplinary efforts from physics, chemistry, and medicine to tackle photochemical dynamics problems relevant to the computational drug discovery of photoactive drugs and sunscreen molecules. This class of molecules is difficult to simulate with conventional computers due to the molecules’ fundamentally quantum mechanical nature. For accurate calculations, the required memory on a classical computer scale exponentially with the number of atoms in the molecules [1]. Although ingenious approximations can simplify calculations, many key problems remain intractable, even on large supercomputers.
Our approach seeks to circumvent the limitations of classical computers by using a well-controlled quantum system to simulate targeted quantum systems efficiently (with linear scaling) [2]: We use individually controllable atoms trapped in high vacuum as fundamental building blocks to study targeted photochemistry problems that are challenging to study through conventional approaches [3].
I will discuss recent proof-of-principle quantum experiments in this direction [4,5]. This includes a ground-breaking work where we design and map a long-standing physical chemistry dynamics problem onto a relatively small quantum device and then slow the process down by a factor of 100 billion times to clearly reveal an interference pattern caused by a geometric structure in chemistry called “conical intersection”. Chemists have tried to directly observe such geometric processes in chemical dynamics since the 1950s, but it is not feasible to observe them directly given the rapid timescales involved, usually in the femtosecond regime. Our experiment demonstrates that our new quantum simulation approach could have the potential to address quantum chemical dynamics problems relevant to computational drug discovery.
References
[1] Quantum mechanics in chemistry (Dover, 2002).
[2] Simulating physics with computers, Int. J. Theor. Phys. 21, 467 (1982).
[3] Analog quantum simulation of chemical dynamics, Chem. Sci. 12, 9794 (2021).
[4] Predicting molecular vibronic spectra using time-domain analog quantum simulation, Chem. Sci. 14, 9439 (2023).
[5] Direct observation of geometric-phase interference in dynamics around a conical intersection, Nat. Chem. 15, 1503 (2023).