The ultimate goal of computational quantum chemistry is to tackle the quantum effects that determine the structure and properties of molecules. Reaching this goal is challenging since the energies associated with these effects are typically a tiny fraction of the total energy of the molecule. One of the applications of computational quantum chemistry is the study and design of drugs that block different stages of the virus’s life cycle. These types of drugs are called anti-retrovirals and they specifically bind with and block a virus protein or protease. With the protease blocked, the virus cannot make more copies of itself. It is important to perform chemical simulations to confirm that anti-retrovirals bind with the virus protein. However, such simulations are hard and sometimes ineffective on classical supercomputers.
Quantum chemistry for HIV
HIV is a virus that has presented a global challenge for public health. This virus has an impact on multiple societal dimensions including nutrition, access to health, education, and research funding. To compound the difficulties, the virus mutates rapidly with different strains having different geographic footprints.
Current supercomputers lack the ability to simulate HIV molecules and hence no treatment has been generated so far. However, quantum computers promise more accurate simulations allowing for a better drug-design workflow. For instance, the Variational Quantum Eigensolver (VQE) is an algorithm for finding the ground-state of a molecule and simulate other chemical phenomena.
How does the VQE algorithm work?
The inputs to the VQE are a molecular Hamiltonian and a parametrized circuit preparing the quantum state of the molecule. If you’re not a physicist, your most probable reaction will be: “what is that?!” Fortunately, you don’t need to know about quantum physics to understand VQEs. So, let me put it into other words. VQE is a hybrid quantum-classical algorithm, which means that the algorithm consists of two stages: a quantum and a classical stage. The output is an approximation of the combination of values that solve a given optimization problem.
During the quantum stage, a trial molecular state is created on the quantum computer. The trial state is specified by a collection of parameters which are provided and adjusted by the classical stage. After the trial state is created, its energy is calculated on the quantum computer. During the classical stage, a classical optimization algorithm looks at the previous energy levels and the new energy level and decides how to adjust the trial state parameters.
This process repeats until the energy essentially stops decreasing. The output of the whole algorithm is the final set of parameters that produces the winning simulation of our molecule and its chemical properties. Using this algorithm, scientists could find the anti-retrovirals that block the HIV virus among many other viruses that are computationally expensive to simulate.
But… what else?
Simulating molecules is only one of the multiple applications that the VQE algorithm offers. Its power is also extended to areas such as Machine Learning (ML) and Artificial Intelligence (AI). These fields rely on processing huge amounts of complex datasets. There is also a need to evolve algorithms to allow for better learning, reasoning, and understanding. While some ML and AI algorithms would take years in a classical supercomputer, a quantum computer would solve it in a matter of seconds using VQE’s. To wrap up, quantum computers are leading the way to the next generation of computers by increasing computational capability and power. With algorithms such as VQE’s, fields such as computational chemistry, AI and Machine Learning will enter a new era of power and speed.
REFERENCES
- Pennylane.ai. 2021. A brief overview of VQE — PennyLane. [online] Available at: <https://pennylane.ai/qml/demos/tutorial_vqe.html> [Accessed 3 October 2021].
• 2021. [online] Available at: <https://towardsdatascience.com/the-variationalquantum-
eigensolver-explained-adcbc9659c3a.> [Accessed 3 October 2021].
• Qiskit.org. 2021. Simulating Molecules using VQE. [online] Available at: <https://
qiskit.org/textbook/ch-applications/vqe-molecules.html> [Accessed 3 October
2021].
Juan Francisco Rodríguez – Quantum Strategist
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