Current Understanding of the Mechanism of Water Oxidation in Photosystem II and Its Relation to XFEL Data.

The investigation of water oxidation in photosynthesis has remained a central topic in biochemical research for the last few decades due to the importance of this catalytic process for technological applications. Significant progress has been made following the 2011 report of a high-resolution X-ray crystallographic structure resolving the site of catalysis, a protein-bound Mn4CaOx complex, which passes through ≥5 intermediate states in the water-splitting cycle. Spectroscopic techniques complemented by quantum chemical calculations aided in understanding the electronic structure of the cofactor in all (detectable) states of the enzymatic process. Together with isotope labeling, these techniques also revealed the binding of the two substrate water molecules to the cluster. These results are described in the context of recent progress using X-ray crystallography with free-electron lasers on these intermediates. The data are instrumental for developing a model for the biological water oxidation cycle.

Moving Through Barriers in Science and Life.

This first serious attempt at an autobiographical accounting has forced me to sit still long enough to compile my thoughts about a long personal and scientific journey. I especially hope that my trajectory will be of interest and perhaps beneficial to much younger women who are just getting started in their careers. To paraphrase from Virginia Woolf's writings in A Room of One's Own at the beginning of the 20th century, "for most of history Anonymous was a Woman." However, Ms. Woolf is also quoted as saying "nothing has really happened until it has been described," a harbinger of the enormous historical changes that were about to be enacted and recorded by women in the sciences and other disciplines. The progress in my chosen field of study-the chemical basis of enzyme action-has also been remarkable, from the first description of an enzyme's 3D structure to a growing and deep understanding of the origins of enzyme catalysis.

Influence of pump laser fluence on ultrafast myoglobin structural dynamics.

High-intensity femtosecond pulses from an X-ray free-electron laser enable pump-probe experiments for the investigation of electronic and nuclear changes during light-induced reactions. On timescales ranging from femtoseconds to milliseconds and for a variety of biological systems, time-resolved serial femtosecond crystallography (TR-SFX) has provided detailed structural data for light-induced isomerization, breakage or formation of chemical bonds and electron transfer1,2. However, all ultrafast TR-SFX studies to date have employed such high pump laser energies that nominally several photons were absorbed per chromophore3-17. As multiphoton absorption may force the protein response into non-physiological pathways, it is of great concern18,19 whether this experimental approach20 allows valid conclusions to be drawn vis-à-vis biologically relevant single-photon-induced reactions18,19. Here we describe ultrafast pump-probe SFX experiments on the photodissociation of carboxymyoglobin, showing that different pump laser fluences yield markedly different results. In particular, the dynamics of structural changes and observed indicators of the mechanistically important coherent oscillations of the Fe-CO bond distance (predicted by recent quantum wavepacket dynamics21) are seen to depend strongly on pump laser energy, in line with quantum chemical analysis. Our results confirm both the feasibility and necessity of performing ultrafast TR-SFX pump-probe experiments in the linear photoexcitation regime. We consider this to be a starting point for reassessing both the design and the interpretation of ultrafast TR-SFX pump-probe experiments20 such that mechanistically relevant insight emerges.

Femtosecond proton transfer in urea solutions probed by X-ray spectroscopy.

Proton transfer is one of the most fundamental events in aqueous-phase chemistry and an emblematic case of coupled ultrafast electronic and structural dynamics1,2. Disentangling electronic and nuclear dynamics on the femtosecond timescales remains a formidable challenge, especially in the liquid phase, the natural environment of biochemical processes. Here we exploit the unique features of table-top water-window X-ray absorption spectroscopy3-6 to reveal femtosecond proton-transfer dynamics in ionized urea dimers in aqueous solution. Harnessing the element specificity and the site selectivity of X-ray absorption spectroscopy with the aid of ab initio quantum-mechanical and molecular-mechanics calculations, we show how, in addition to the proton transfer, the subsequent rearrangement of the urea dimer and the associated change of the electronic structure can be identified with site selectivity. These results establish the considerable potential of flat-jet, table-top X-ray absorption spectroscopy7,8 in elucidating solution-phase ultrafast dynamics in biomolecular systems.

Topological triple phase transition in non-Hermitian Floquet quasicrystals.

Phase transitions connect different states of matter and are often concomitant with the spontaneous breaking of symmetries. An important category of phase transitions is mobility transitions, among which is the well known Anderson localization1, where increasing the randomness induces a metal-insulator transition. The introduction of topology in condensed-matter physics2-4 lead to the discovery of topological phase transitions and materials as topological insulators5. Phase transitions in the symmetry of non-Hermitian systems describe the transition to on-average conserved energy6 and new topological phases7-9. Bulk conductivity, topology and non-Hermitian symmetry breaking seemingly emerge from different physics and, thus, may appear as separable phenomena. However, in non-Hermitian quasicrystals, such transitions can be mutually interlinked by forming a triple phase transition10. Here we report the experimental observation of a triple phase transition, where changing a single parameter simultaneously gives rise to a localization (metal-insulator), a topological and parity-time symmetry-breaking (energy) phase transition. The physics is manifested in a temporally driven (Floquet) dissipative quasicrystal. We implement our ideas via photonic quantum walks in coupled optical fibre loops11. Our study highlights the intertwinement of topology, symmetry breaking and mobility phase transitions in non-Hermitian quasicrystalline synthetic matter. Our results may be applied in phase-change devices, in which the bulk and edge transport and the energy or particle exchange with the environment can be predicted and controlled.

Brain-inspired computing needs a master plan.

New computing technologies inspired by the brain promise fundamentally different ways to process information with extreme energy efficiency and the ability to handle the avalanche of unstructured and noisy data that we are generating at an ever-increasing rate. To realize this promise requires a brave and coordinated plan to bring together disparate research communities and to provide them with the funding, focus and support needed. We have done this in the past with digital technologies; we are in the process of doing it with quantum technologies; can we now do it for brain-inspired computing?

Quantum-enhanced nonlinear microscopy.

The performance of light microscopes is limited by the stochastic nature of light, which exists in discrete packets of energy known as photons. Randomness in the times that photons are detected introduces shot noise, which fundamentally constrains sensitivity, resolution and speed1. Although the long-established solution to this problem is to increase the intensity of the illumination light, this is not always possible when investigating living systems, because bright lasers can severely disturb biological processes2-4. Theory predicts that biological imaging may be improved without increasing light intensity by using quantum photon correlations1,5. Here we experimentally show that quantum correlations allow a signal-to-noise ratio beyond the photodamage limit of conventional microscopy. Our microscope is a coherent Raman microscope that offers subwavelength resolution and incorporates bright quantum correlated illumination. The correlations allow imaging of molecular bonds within a cell with a 35 per cent improved signal-to-noise ratio compared with conventional microscopy, corresponding to a 14 per cent improvement in concentration sensitivity. This enables the observation of biological structures that would not otherwise be resolved. Coherent Raman microscopes allow highly selective biomolecular fingerprinting in unlabelled specimens6,7, but photodamage is a major roadblock for many applications8,9. By showing that the photodamage limit can be overcome, our work will enable order-of-magnitude improvements in the signal-to-noise ratio and the imaging speed.

Few-fs resolution of a photoactive protein traversing a conical intersection.

The structural dynamics of a molecule are determined by the underlying potential energy landscape. Conical intersections are funnels connecting otherwise separate potential energy surfaces. Posited almost a century ago1, conical intersections remain the subject of intense scientific interest2-5. In biology, they have a pivotal role in vision, photosynthesis and DNA stability6. Accurate theoretical methods for examining conical intersections are at present limited to small molecules. Experimental investigations are challenged by the required time resolution and sensitivity. Current structure-dynamical understanding of conical intersections is thus limited to simple molecules with around ten atoms, on timescales of about 100 fs or longer7. Spectroscopy can achieve better time resolutions8, but provides indirect structural information. Here we present few-femtosecond, atomic-resolution videos of photoactive yellow protein, a 2,000-atom protein, passing through a conical intersection. These videos, extracted from experimental data by machine learning, reveal the dynamical trajectories of de-excitation via a conical intersection, yield the key parameters of the conical intersection controlling the de-excitation process and elucidate the topography of the electronic potential energy surfaces involved.

New classifications for quantum bioinformatics: Q-bioinformatics, QCt-bioinformatics, QCg-bioinformatics, and QCr-bioinformatics.

Bioinformatics has revolutionized biology and medicine by using computational methods to analyze and interpret biological data. Quantum mechanics has recently emerged as a promising tool for the analysis of biological systems, leading to the development of quantum bioinformatics. This new field employs the principles of quantum mechanics, quantum algorithms, and quantum computing to solve complex problems in molecular biology, drug design, and protein folding. However, the intersection of bioinformatics, biology, and quantum mechanics presents unique challenges. One significant challenge is the possibility of confusion among scientists between quantum bioinformatics and quantum biology, which have similar goals and concepts. Additionally, the diverse calculations in each field make it difficult to establish boundaries and identify purely quantum effects from other factors that may affect biological processes. This review provides an overview of the concepts of quantum biology and quantum mechanics and their intersection in quantum bioinformatics. We examine the challenges and unique features of this field and propose a classification of quantum bioinformatics to promote interdisciplinary collaboration and accelerate progress. By unlocking the full potential of quantum bioinformatics, this review aims to contribute to our understanding of quantum mechanics in biological systems.

Femtosecond-to-millisecond structural changes in a light-driven sodium pump.

Light-driven sodium pumps actively transport small cations across cellular membranes1. These pumps are used by microorganisms to convert light into membrane potential and have become useful optogenetic tools with applications in neuroscience. Although the resting state structures of the prototypical sodium pump Krokinobacter eikastus rhodopsin 2 (KR2) have been solved2,3, it is unclear how structural alterations over time allow sodium to be translocated against a concentration gradient. Here, using the Swiss X-ray Free Electron Laser4, we have collected serial crystallographic data at ten pump-probe delays from femtoseconds to milliseconds. High-resolution structural snapshots throughout the KR2 photocycle show how retinal isomerization is completed on the femtosecond timescale and changes the local structure of the binding pocket in the early nanoseconds. Subsequent rearrangements and deprotonation of the retinal Schiff base open an electrostatic gate in microseconds. Structural and spectroscopic data, in combination with quantum chemical calculations, indicate that a sodium ion binds transiently close to the retinal within one millisecond. In the last structural intermediate, at 20 milliseconds after activation, we identified a potential second sodium-binding site close to the extracellular exit. These results provide direct molecular insight into the dynamics of active cation transport across biological membranes.

Spin-enhanced nanodiamond biosensing for ultrasensitive diagnostics.

The quantum spin properties of nitrogen-vacancy defects in diamond enable diverse applications in quantum computing and communications1. However, fluorescent nanodiamonds also have attractive properties for in vitro biosensing, including brightness2, low cost3 and selective manipulation of their emission4. Nanoparticle-based biosensors are essential for the early detection of disease, but they often lack the required sensitivity. Here we investigate fluorescent nanodiamonds as an ultrasensitive label for in vitro diagnostics, using a microwave field to modulate emission intensity5 and frequency-domain analysis6 to separate the signal from background autofluorescence7, which typically limits sensitivity. Focusing on the widely used, low-cost lateral flow format as an exemplar, we achieve a detection limit of 8.2 × 10-19 molar for a biotin-avidin model, 105 times more sensitive than that obtained using gold nanoparticles. Single-copy detection of HIV-1 RNA can be achieved with the addition of a 10-minute isothermal amplification step, and is further demonstrated using a clinical plasma sample with an extraction step. This ultrasensitive quantum diagnostics platform is applicable to numerous diagnostic test formats and diseases, and has the potential to transform early diagnosis of disease for the benefit of patients and populations.

The complexities of ligand/receptor interactions: Exploring the role of molecular vibrations and quantum tunnelling.

Molecular vibrations and quantum tunneling may link ligand binding to the function of pharmacological receptors. The well-established lock-and-key model explains a ligand's binding and recognition by a receptor; however, a general mechanism by which receptors translate binding into activation, inactivation, or modulation remains elusive. The Vibration Theory of Olfaction was proposed in the 1930s to explain this subset of receptor-mediated phenomena by correlating odorant molecular vibrations to smell, but a mechanism was lacking. In the 1990s, inelastic electron tunneling was proposed as a plausible mechanism for translating molecular vibration to odorant physiology. More recently, studies of ligands' vibrational spectra and the use of deuterated ligand analogs have provided helpful information to study this admittedly controversial hypothesis in metabotropic receptors other than olfactory receptors. In the present work, based in part on published experiments from our laboratory using planarians as an experimental organism, I will present a rationale and possible experimental approach for extending this idea to ligand-gated ion channels.

Free energies at QM accuracy from force fields via multimap targeted estimation.

Accurate predictions of ligand binding affinities would greatly accelerate the first stages of drug discovery campaigns. However, using highly accurate interatomic potentials based on quantum mechanics (QM) in free energy methods has been so far largely unfeasible due to their prohibitive computational cost. Here, we present an efficient method to compute QM free energies from simulations using cheap reference potentials, such as force fields (FFs). This task has traditionally been out of reach due to the slow convergence of computing the correction from the FF to the QM potential. To overcome this bottleneck, we generalize targeted free energy methods to employ multiple maps-implemented with normalizing flow neural networks (NNs)-that maximize the overlap between the distributions. Critically, the method requires neither a separate expensive training phase for the NNs nor samples from the QM potential. We further propose a one-epoch learning policy to efficiently avoid overfitting, and we combine our approach with enhanced sampling strategies to overcome the pervasive problem of poor convergence due to slow degrees of freedom. On the drug-like molecules in the HiPen dataset, the method accelerates the calculation of the free energy difference of switching from an FF to a DFTB3 potential by three orders of magnitude compared to standard free energy perturbation and by a factor of eight compared to previously published nonequilibrium calculations. Our results suggest that our method, in combination with efficient QM/MM calculations, may be used in lead optimization campaigns in drug discovery and to study protein-ligand molecular recognition processes.

A deep transfer learning-based protocol accelerates full quantum mechanics calculation of protein.

Effective full quantum mechanics (FQM) calculation of protein remains a grand challenge and of great interest in computational biology with substantial applications in drug discovery, protein dynamic simulation and protein folding. However, the huge computational complexity of the existing QM methods impends their applications in large systems. Here, we design a transfer-learning-based deep learning (TDL) protocol for effective FQM calculations (TDL-FQM) on proteins. By incorporating a transfer-learning algorithm into deep neural network (DNN), the TDL-FQM protocol is capable of performing calculations at any given accuracy using models trained from small datasets with high-precision and knowledge learned from large amount of low-level calculations. The high-level double-hybrid DFT functional and high-level quality of basis set is used in this work as a case study to evaluate the performance of TDL-FQM, where the selected 15 proteins are predicted to have a mean absolute error of 0.01 kcal/mol/atom for potential energy and an average root mean square error of 1.47 kcal/mol/$ {\rm A^{^{ \!\!\!o}}} $ for atomic forces. The proposed TDL-FQM approach accelerates the FQM calculation more than thirty thousand times faster in average and presents more significant benefits in efficiency as the size of protein increases. The ability to learn knowledge from one task to solve related problems demonstrates that the proposed TDL-FQM overcomes the limitation of standard DNN and has a strong power to predict proteins with high precision, which solves the challenge of high precision prediction in large chemical and biological systems.

Quantum annealing-based clustering of single cell RNA-seq data.

Cluster analysis is a crucial stage in the analysis and interpretation of single-cell gene expression (scRNA-seq) data. It is an inherently ill-posed problem whose solutions depend heavily on hyper-parameter and algorithmic choice. The popular approach of K-means clustering, for example, depends heavily on the choice of K and the convergence of the expectation-maximization algorithm to local minima of the objective. Exhaustive search of the space for multiple good quality solutions is known to be a complex problem. Here, we show that quantum computing offers a solution to exploring the cost function of clustering by quantum annealing, implemented on a quantum computing facility offered by D-Wave [1]. Out formulation extracts minimum vertex cover of an affinity graph to sub-sample the cell population and quantum annealing to optimise the cost function. A distribution of low-energy solutions can thus be extracted, offering alternate hypotheses about how genes group together in their space of expressions.

Mobility of sodium ions in agarose gels probed through combined single- and triple-quantum NMR.

Metal ions, including biologically prevalent sodium ions, can modulate electrostatic interactions frequently involved in the stability of condensed compartments in cells. Quantitative characterization of heterogeneous ion dynamics inside biomolecular condensates demands new experimental approaches. Here we develop a 23Na NMR relaxation-based integrative approach to probe dynamics of sodium ions inside agarose gels as a model system. We exploit the electric quadrupole moment of spin-3/2 23Na nuclei and, through combination of single-quantum and triple-quantum-filtered 23Na NMR relaxation methods, disentangle the relaxation contribution of different populations of sodium ions inside gels. Three populations of sodium ions are identified: a population with bi-exponential relaxation representing ions within the slow motion regime and two populations with mono-exponential relaxation but at different rates. Our study demonstrates the dynamical heterogeneity of sodium ions inside agarose gels and presents a new experimental approach for monitoring dynamics of sodium and other spin-3/2 ions (e.g. chloride) in condensed environments.

Quantum critical behaviour at the many-body localization transition.

Phase transitions are driven by collective fluctuations of a system's constituents that emerge at a critical point1. This mechanism has been extensively explored for classical and quantum systems in equilibrium, whose critical behaviour is described by the general theory of phase transitions. Recently, however, fundamentally distinct phase transitions have been discovered for out-of-equilibrium quantum systems, which can exhibit critical behaviour that defies this description and is not well understood1. A paradigmatic example is the many-body localization (MBL) transition, which marks the breakdown of thermalization in an isolated quantum many-body system as its disorder increases beyond a critical value2-11. Characterizing quantum critical behaviour in an MBL system requires probing its entanglement over space and time4,5,7, which has proved experimentally challenging owing to stringent requirements on quantum state preparation and system isolation. Here we observe quantum critical behaviour at the MBL transition in a disordered Bose-Hubbard system and characterize its entanglement via its multi-point quantum correlations. We observe the emergence of strong correlations, accompanied by the onset of anomalous diffusive transport throughout the system, and verify their critical nature by measuring their dependence on the system size. The correlations extend to high orders in the quantum critical regime and appear to form via a sparse network of many-body resonances that spans the entire system12,13. Our results connect the macroscopic phenomenology of the transition to the system's microscopic structure of quantum correlations, and they provide an essential step towards understanding criticality and universality in non-equilibrium systems1,7,13.

Catalytic mechanism and pH dependence of a methyltransferase ribozyme (MTR1) from computational enzymology.

A methyltransferase ribozyme (MTR1) was selected in vitro to catalyze alkyl transfer from exogenous O6-methylguanine (O6mG) to a target adenine N1, and recently, high-resolution crystal structures have become available. We use a combination of classical molecular dynamics, ab initio quantum mechanical/molecular mechanical (QM/MM) and alchemical free energy (AFE) simulations to elucidate the atomic-level solution mechanism of MTR1. Simulations identify an active reactant state involving protonation of C10 that hydrogen bonds with O6mG:N1. The deduced mechanism involves a stepwise mechanism with two transition states corresponding to proton transfer from C10:N3 to O6mG:N1 and rate-controlling methyl transfer (19.4 kcal·mol-1 barrier). AFE simulations predict the pKa for C10 to be 6.3, close to the experimental apparent pKa of 6.2, further implicating it as a critical general acid. The intrinsic rate derived from QM/MM simulations, together with pKa calculations, enables us to predict an activity-pH profile that agrees well with experiment. The insights gained provide further support for a putative RNA world and establish new design principles for RNA-based biochemical tools.

Direct free energy evaluation of classical and quantum many-body systems via field-theoretic simulation.

Free energy evaluation in molecular simulations of both classical and quantum systems is computationally intensive and requires sophisticated algorithms. This is because free energy depends on the volume of accessible phase space, a quantity that is inextricably linked to the integration measure in a coordinate representation of a many-body problem. In contrast, the same problem expressed as a field theory (auxiliary field or coherent states) isolates the particle number as a simple parameter in the Hamiltonian or action functional and enables the identification of a chemical potential field operator. We show that this feature leads a "direct" method of free energy evaluation, in which a particle model is converted to a field theory and appropriate field operators are averaged using a field-theoretic simulation conducted with complex Langevin sampling. These averages provide an immediate estimate of the Helmholtz free energy in the canonical ensemble and the entropy in the microcanonical ensemble. The method is illustrated for a classical polymer solution, a block copolymer melt exhibiting liquid crystalline and solid mesophases, and a quantum fluid of interacting bosons.

Interference of nuclear wavepackets in a pair of proton transfer reactions.

Quantum mechanics revolutionized chemists' understanding of molecular structure. In contrast, the kinetics of molecular reactions in solution are well described by classical, statistical theories. To reveal how the dynamics of chemical systems transition from quantum to classical, we study femtosecond proton transfer in a symmetric molecule with two identical reactant sites that are spatially apart. With the reaction launched from a superposition of two local basis states, we hypothesize that the ensuing motions of the electrons and nuclei will proceed, conceptually, in lockstep as a superposition of probability amplitudes until decoherence collapses the system to a product. Using ultrafast spectroscopy, we observe that the initial superposition state affects the reaction kinetics by an interference mechanism. With the aid of a quantum dynamics model, we propose how the evolution of nuclear wavepackets manifests the unusual intersite quantum correlations during the reaction.