Quantum biology

The role of computational biochemistry in understanding and quantifying the quantum nature of life and biological systems cannot be overestimated. At Surrey, we have paved the way for innovative approaches in this area, in particular for understanding the role of proton tunnelling and de-localisation in the creation of point defects in DNA, which could have implications for cancer research as well as helping us understand the rate of evolution.

There is still considerable work to do using computational approaches, which include quantum chemistry combined with multi-scale simulations and open quantum system theory. Among those long-term goals are:

• The definition and calculation of entropy in biological systems, especially in DNA, with its connection with information theory and quantum entropy.
• The role of quantum effects in propagating or correcting genetic errors.
• The interaction of light and electromagnetic radiation with DNA and its role in generating DNA damage through coherent quantum processes.

To progress on these problems, computational methods need to be applied in conjunction with state-of-the-art experimental techniques such as time-resolved spectroscopy and ultrafast scattering. Close collaboration of chemists, mathematicians and theoretical physicists is essential as new methods and algorithms are developed to elucidate the connection between purely quantum particles (electrons and protons) and classical environments such as proteins, solvents and ligands.

One of the most vibrant areas of research in quantum biology, and in which the team at Surrey is world leading, is the study of proton tunnelling in DNA. Proton transfer across hydrogen bonds in DNA can produce non-canonical nucleobase dimers and is a possible source of single-point mutations when these forms mismatch under replication.

Previous computational studies by the group have revealed this process to be energetically feasible for the guanine-cytosine (GC) base pair, but the tautomeric product (GC) is short-lived.

Using a combination of computational chemistry (density functional theory and multi-scale quantum mechanical/molecular dynamics (QM/MM) simulations) together with an open quantum systems approach to account for the cellular environment, we model this process, including the effect of the replisome enzymes on proton transfer during strand separation and replication.

The interaction of a quantum system with its surroundings has major implications on its evolution and can significantly limit our ability to exploit quantum degrees of freedom for advanced applications. Understanding the environment-mediated tendency of quantum mechanical systems to decohere and lose their non-classical correlations is of utmost importance and may open avenues yet to be explored for addressing basic physics questions and practical quantum-technology applications.

In parallel, in the emerging field of quantum biology, there is a growing body of evidence that in certain bio-molecular complexes, quantum effects dominate over their purely classical correspondents, especially in the case of photo-excited systems for which the surrounding dielectric environment plays an essential role in the system dynamics.

We are currently exploring the physical phenomena associated with the dynamical decoherence of the chromophores within a green fluorescent protein coupled to a finite-temperature dielectric environment, a system of significant interest due to its anomalously long coherence lifetimes.

We are focusing our investigation on the degree of coherence displayed by independent green fluorescent-protein chromophores and the energy-transfer dynamics mediated by dielectric relaxation of the environment, with the aim of understanding long coherence lifetimes in these systems.

Mankind is facing the greatest ever challenge to its prosperity from the rapid and devastating advancement of the impact of climate change. The threats caused by climate change are multitudinous; predominant among them is food security. Green plants form the basis of almost all food chains on earth, but conditions for their growth are changing too rapidly for them to adapt.

Understanding efficiencies and capabilities of plants is acutely important, and this demands the development of a novel mathematical framework that enables us to infer conditions under which plants can adapt to changing environmental conditions. By applying and extending the mathematical theory of quantum signal detection, one can characterise dynamic behaviours of green plants. These models in turn enable us to measure information contents of environmental messages experienced by plants, and to estimate the computational efficiencies of plants.

Such estimates are important because different species are likely to process information with different efficiencies, with considerable consequences for agriculture; for an ecological understanding of invasive plants; and more generally for responses to environmental changes that lead to ecological stability.

Now, if there are conflicting environmental cues reaching a green plant, then the classical theory of signal detection fails to capture the dynamical features adequately. Nevertheless, their quantum counterpart, represented by a certain class of stochastic Schrödinger equations, can model such situations.

This project therefore explores computational capabilities of green plants (and other biological systems), while at the same time examining mathematical structures and physical implications of stochastic Schrödinger equations that give rise to Lindblad equations of open quantum systems.