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Fung, R.

Publications and source records attributed to Fung, R..

3 recordsLinked to original sources

Single-femtosecond atomic-resolution observation of a 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 energy surfaces. Posited almost a century ago 1, conical intersections remain the subject of intense scientific investigation 2-4. In biology, they play a pivotal role in vision, photosynthesis, and DNA stability 5,6. In ultrafast radiationless de-excitation 1,7, they are vital to ameliorating photon-induced damage. In chemistry, they tightly couple the normally separable nuclear and electronic degrees of freedom, precluding the Born-Oppenheimer approximation 8. In physics, they manifest a Berry phase, giving rise to destructive interference between clockwise and anti-clockwise trajectories around the conical intersection 9. 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 10 atoms, on timescales of about 100 fs or longer 10. Spectroscopy can achieve better time resolution, but provides only indirect structural information. Here, we present single-femtosecond, atomic-resolution movies of a 2,000-atom protein passing through a conical intersection. These movies, extracted from experimental data by geometric 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.

biophysics↗

Hits-Based Quantitative Characterization of SOBI-Recovered P3 Network Configuration: an EEG Source-Imaging Study

One frequently studied biomarker for health and disease conditions is the P3 component extracted from scalp recorded electroencephalography (EEG). The spatial origin of this significant neural signal is known to be distributed, typically involving large regions of the cerebral cortex as well as subcortical structures. Unlike the temporal characterization of the P3 by amplitude or latency measures from event-related potentials (ERPs), the spatial characterization of the P3 component is relatively rare, typically qualitative, and often reported as differences between populations (group differences between healthy controls and clinical groups). Here we introduce a novel approach to quantitatively characterize the spatial origin of the P3 component by (1) applying second-order blind identification (SOBI) to continuous, high-density EEG data to extract the P3 component, (2) modeling the underlying generators of the SOBI P3 component as a set of equivalent current dipoles (ECDs) in Talairach space using BESA; (3) using the application Talairach Client to determine the "hits" associated with the anatomical structures at three level of resolution (lobe, gyrus, and cell type). We show that the hits information provided by Talairach Client can enable a quantitative characterization of the spatial configuration of the network underlying the P3 component (P3N) via two quantities: cross-individual reliability (or consistency) of a given brain structure as a part of the P3N, and within-individual contribution of a given brain structure to the whole P3N network. We suggest that this method may be used to further differentiate individuals in the absence of differences in P3 amplitude or latency, or when scientific questions or practical application cannot be supported by a yes-no answer regarding the source of a P3 component. Finally, application of our method to a group of 13 participants revealed that frontal structures, particularly BA10, play a special role in the function of a global cortical network underlying novelty processing.

neuroscience↗

Authentic Enzyme Intermediates Captured "on-the-fly" by Mix-and-Inject Serial Crystallography

Ever since the first atomic structure of an enzyme was solved, the discovery of the mechanism and dynamics of reactions catalyzed by biomolecules has been the key goal for the understanding of the molecular processes that drive life on earth. Despite a large number of successful methods for trapping reaction intermediates, the direct observation of an ongoing reaction has been possible only in rare and exceptional cases. Here, we demonstrate a general method for capturing enzyme catalysis in-action by mix-and-inject serial crystallography. Specifically, we follow the catalytic reaction of the Mycobacterium tuberculosis -lactamase with the 3rd generation antibiotic ceftriaxone by time-resolved serial femtosecond crystallography. The results reveal, in near atomic detail, antibiotic cleavage and inactivation on the millisecond to second time scales including the crossover from transition state kinetics to steady-state kinetics.\n\nSynopsisAn enzymatically catalyzed reaction is initiated by diffusion based mixing of substrate and followed at runtime by time-resolved serial crystallography using a free electron laser.

biophysics↗