Quantum Computing for Molecular Biology

• Published in: Chembiochem : a European journal of chemical biology 2023-07, Vol.24 (13), p.e202300120-n/a
• Main Authors: Baiardi, Alberto, Christandl, Matthias, Reiher, Markus
• Format: Article
• Language: English
• Subjects: Bioinformatics; Biology; Biomolecules; Classical mechanics; Computer applications; Computing Methodologies; Drug development; Electronic structure; Molecular Biology; Molecular Dynamics Simulation; Molecular Simulations; Molecular Structure; Protein folding; Quantum Biology; Quantum Chemistry; Quantum Computing; Quantum mechanics; Quantum Theory
• ISSN: 1439-4227; 1439-7633
• DOI: 10.1002/cbic.202300120

Molecular biology and biochemistry interpret microscopic processes in the living world in terms of molecular structures and their interactions, which are quantum mechanical by their very nature. Whereas the theoretical foundations of these interactions are well established, the computational solution of the relevant quantum mechanical equations is very hard. However, much of molecular function in biology can be understood in terms of classical mechanics, where the interactions of electrons and nuclei have been mapped onto effective classical surrogate potentials that model the interaction of atoms or even larger entities. The simple mathematical structure of these potentials offers huge computational advantages; however, this comes at the cost that all quantum correlations and the rigorous many‐particle nature of the interactions are omitted. In this work, we discuss how quantum computation may advance the practical usefulness of the quantum foundations of molecular biology by offering computational advantages for simulations of biomolecules. We not only discuss typical quantum mechanical problems of the electronic structure of biomolecules in this context, but also consider the dominating classical problems (such as protein folding and drug design) as well as data‐driven approaches of bioinformatics and the degree to which they might become amenable to quantum simulation and quantum computation. A road map for quantum computing in molecular biology with a potentially ground‐breaking quantum advantage is presented. Key concepts are introduced to connect the terminology of biology, chemistry, physics, and computer science that are all relevant for this transdisciplinary endeavor. Molecular simulations of biochemical reactions are the most promising target, but quantum computing might also benefit data‐driven approaches and structure prediction of biomacromolecules.