Quantum Computing for Molecular Biology**

Abstract

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 advan-tages; 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 Vision for the Future of Multiscale Modeling

“…Furthermore, the modeling capabilities for quantum systems expected from the evolution of QC approaches are astonishing. 315,316 The direct application of quantum-based calculators instead of classical ones promises a further leap toward higher accuracy and reliability in quantum calculations. The possibility of combining classical and quantum computers in order to harness the strengths of each (similar to CPU and GPU usage in current-era calculations), could introduce a novel concept of multiscale computation.…”

“…Such experimental and theoretical techniques make use of atomistically sharp plasmonic tips of scanning probe microscopes to manipulate and probe single molecules by combining tunneling electrons and visible light, thus achieving submolecular resolution thanks to plasmonic field effects. − The presence of such metallic tips can be suitably modeled by Continuum methods (Figure b), hence we believe that a proper combination of the QM/MM novel implementations above-mentioned with a continuum description of plasmonic objects will pave the way for accurate space- and time-resolved analysis of energy funneling and transport dynamics over long paths in realistic light harvesting complexes. ,− Once implemented, such ideas could open new horizons for computational studies in physical chemistry, that currently still rely on heavy and insight-based partitioning of the studied chemical problems, inevitably leading to discrepancies in the experimental-theoretical comparison. Furthermore, the modeling capabilities for quantum systems expected from the evolution of QC approaches are astonishing. , The direct application of quantum-based calculators instead of classical ones promises a further leap toward higher accuracy and reliability in quantum calculations. The possibility of combining classical and quantum computers in order to harness the strengths of each (similar to CPU and GPU usage in current-era calculations), could introduce a novel concept of multiscale computation.…”

Control Flow in Active Inference Systems—Part I: Classical and Quantum Formulations of Active Inference

“…While the "quantum" nature of proteins and other macromolecules is broadly acknowledged, the scale at which quantum effects are important remains controversial, with straightforward single-molecule decoherence models predicting decoherence times of attoseconds (10 −18 s) or less [85], [86]: several orders of magnitude below the timescales of processes involved in molecular information processing [87]. While functional roles for quantum coherence in intramolecular information processing have been demonstrated, intermolecular coherence remains experimentally elusive [88]- [91].…”

Quantum computing on nucleic acid research: Approaching towards next-generation computing

“…Quantum chemistry is solving complicated problems of chemistry, especially biochemistry, such as molecular recognition, protein folding, structural biology, advanced drug discovery, etc. 9 , 13 , 14 , 15 One of the most promising fields is quantum computational chemistry, a bright field for solving biochemical problems. It uses the knowledge of both computational chemistry and quantum computing.…”