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Femtosecond-to-millisecond structural changes in a light-driven sodium pump 期刊论文
NATURE, 2020, 583 (7815) : 314-+
作者:  Moore, Luiza;  Leongamornlert, Daniel;  Coorens, Tim H. H.;  Sanders, Mathijs A.;  Ellis, Peter;  Dentro, Stefan C.;  Dawson, Kevin J.;  Butler, Tim;  Rahbari, Raheleh;  Mitchell, Thomas J.;  Maura, Francesco;  Nangalia, Jyoti;  Tarpey, Patrick S.;  Brunner, Simon F.;  Lee-Six, Henry;  Hooks, Yvette;  Moody, Sarah;  Mahbubani, Krishnaa T.;  Jimenez-Linan, Mercedes;  Brosens, Jan J.;  Iacobuzio-Donahue, Christine A.;  Martincorena, Inigo;  Saeb-Parsy, Kourosh;  Campbell, Peter J.;  Stratton, Michael R.
收藏  |  浏览/下载:17/0  |  提交时间:2020/07/03

Light-driven sodium pumps actively transport small cations across cellular membranes(1). 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 solved(2,3), it is unclear how structural alterations overtime allow sodium to be translocated against a concentration gradient. Here, using the Swiss X-ray Free Electron Laser(4), 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 bind stransiently 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.


  
General synthesis of two-dimensional van der Waals heterostructure arrays 期刊论文
NATURE, 2020: 368-+
作者:  Bloch, Joel S.;  Pesciullesi, Giorgio;  Boilevin, Jeremy;  Nosol, Kamil;  Irobalieva, Rossitza N.;  Darbre, Tamis;  Aebi, Markus;  Kossiakoff, Anthony A.;  Reymond, Jean-Louis;  Locher, Kaspar P.
收藏  |  浏览/下载:62/0  |  提交时间:2020/07/03

Two-dimensional van der Waals heterostructures (vdWHs) have attracted considerable interest(1-4). However, most vdWHs reported so far are created by an arduous micromechanical exfoliation and manual restacking process(5), which-although versatile for proof-of-concept demonstrations(6-16) and fundamental studies(17-30)-is clearly not scalable for practical technologies. Here we report a general synthetic strategy for two-dimensional vdWH arrays between metallic transition-metal dichalcogenides (m-TMDs) and semiconducting TMDs (s-TMDs). By selectively patterning nucleation sites on monolayer or bilayer s-TMDs, we precisely control the nucleation and growth of diverse m-TMDs with designable periodic arrangements and tunable lateral dimensions at the predesignated spatial locations, producing a series of vdWH arrays, including VSe2/WSe2, NiTe2/WSe2, CoTe2/WSe2, NbTe2/WSe2, VS2/WSe2, VSe2/MoS2 and VSe2/WS2. Systematic scanning transmission electron microscopy studies reveal nearly ideal vdW interfaces with widely tunable moire superlattices. With the atomically clean vdW interface, we further show that the m-TMDs function as highly reliable synthetic vdW contacts for the underlying WSe2 with excellent device performance and yield, delivering a high ON-current density of up to 900 microamperes per micrometre in bilayer WSe2 transistors. This general synthesis of diverse two-dimensional vdWH arrays provides a versatile material platform for exploring exotic physics and promises a scalable pathway to high-performance devices.


A general strategy for the synthesis of two-dimensional van der Waals heterostructure arrays is used to produce high-performance electronic devices, showing the potential of this scalable approach for practical technologies.


  
Power generation from ambient humidity using protein nanowires 期刊论文
NATURE, 2020, 578 (7796) : 550-+
作者:  Luong, Duy X.;  Bets, Ksenia V.;  Algozeeb, Wala Ali;  Stanford, Michael G.;  Kittrell, Carter;  Chen, Weiyin;  Salvatierra, Rodrigo V.;  Ren, Muqing;  McHugh, Emily A.;  Advincula, Paul A.;  Wang, Zhe;  Bhatt, Mahesh;  Guo, Hua;  Mancevski, Vladimir;  Shahsavari, Rouzbeh;  Yakobson, Boris I.;  Tour, James M.
收藏  |  浏览/下载:85/0  |  提交时间:2020/07/03

Harvesting energy from the environment offers the promise of clean power for self-sustained systems(1,2). Known technologies-such as solar cells, thermoelectric devices and mechanical generators-have specific environmental requirements that restrict where they can be deployed and limit their potential for continuous energy production(3-5). The ubiquity of atmospheric moisture offers an alternative. However, existing moisture-based energy-harvesting technologies can produce only intermittent, brief (shorter than 50 seconds) bursts of power in the ambient environment, owing to the lack of a sustained conversion mechanism(6-12). Here we show that thin-film devices made from nanometre-scale protein wires harvested from the microbe Geobacter sulfurreducens can generate continuous electric power in the ambient environment. The devices produce a sustained voltage of around 0.5 volts across a 7-micrometre-thick film, with a current density of around 17 microamperes per square centimetre. We find the driving force behind this energy generation to be a self-maintained moisture gradient that forms within the film when the film is exposed to the humidity that is naturally present in air. Connecting several devices linearly scales up the voltage and current to power electronics. Our results demonstrate the feasibility of a continuous energy-harvesting strategy that is less restricted by location or environmental conditions than other sustainable approaches.


A new type of energy-harvesting device, based on protein nanowires from the microbe Geobacter sulforreducens, can generate a sustained power output by producing a moisture gradient across the nanowire film using natural humidity.


  
Improved protein structure prediction using potentials from deep learning 期刊论文
NATURE, 2020, 577 (7792) : 706-+
作者:  Ma, Runze;  Cao, Duanyun;  Zhu, Chongqin;  Tian, Ye;  Peng, Jinbo;  Guo, Jing;  Chen, Ji;  Li, Xin-Zheng;  Francisco, Joseph S.;  Zeng, Xiao Cheng;  Xu, Li-Mei;  Wang, En-Ge;  Jiang, Ying
收藏  |  浏览/下载:143/0  |  提交时间:2020/07/03

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence(1). This problem is of fundamental importance as the structure of a protein largely determines its function(2)  however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures(3). Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force(4) that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction(5) (CASP13)-a blind assessment of the state of the field-AlphaFold created high-accuracy structures (with template modelling (TM) scores(6) of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined(7).